Bereskie Ty, Haider Husnain, Rodriguez Manuel J, Sadiq Rehan
School of Engineering, Okanagan Campus, University of British Columbia, 1137 Alumni Ave, Kelowna, BC, V1V 1V7, Canada.
Civil Engineering Department, College of Engineering, Qassim University, Buradyah, Qassim, 52571, Saudi Arabia.
Environ Monit Assess. 2017 Aug 23;189(9):464. doi: 10.1007/s10661-017-6176-z.
Traditional approaches for benchmarking drinking water systems are binary, based solely on the compliance and/or non-compliance of one or more water quality performance indicators against defined regulatory guidelines/standards. The consequence of water quality failure is dependent on location within a water supply system as well as time of the year (i.e., season) with varying levels of water consumption. Conventional approaches used for water quality comparison purposes fail to incorporate spatiotemporal variability and degrees of compliance and/or non-compliance. This can lead to misleading or inaccurate performance assessment data used in the performance benchmarking process. In this research, a hierarchical risk-based water quality performance benchmarking framework is proposed to evaluate small drinking water systems (SDWSs) through cross-comparison amongst similar systems. The proposed framework (R framework) is designed to quantify consequence associated with seasonal and location-specific water quality issues in a given drinking water supply system to facilitate more efficient decision-making for SDWSs striving for continuous performance improvement. Fuzzy rule-based modelling is used to address imprecision associated with measuring performance based on singular water quality guidelines/standards and the uncertainties present in SDWS operations and monitoring. This proposed R framework has been demonstrated using data collected from 16 SDWSs in Newfoundland and Labrador and Quebec, Canada, and compared to the Canadian Council of Ministers of the Environment WQI, a traditional, guidelines/standard-based approach. The study found that the R framework provides an in-depth state of water quality and benchmarks SDWSs more rationally based on the frequency of occurrence and consequence of failure events.
传统的饮用水系统基准测试方法是二元的，仅基于一个或多个水质性能指标是否符合既定的监管指南/标准。水质不达标的后果取决于供水系统中的位置以及一年中的时间（即季节），用水量也各不相同。用于水质比较目的的传统方法未能纳入时空变异性以及达标和/或不达标程度。这可能导致在性能基准测试过程中使用误导性或不准确的性能评估数据。在本研究中，提出了一种基于风险的分层水质性能基准测试框架，通过在类似系统之间进行交叉比较来评估小型饮用水系统（SDWSs）。所提出的框架（R框架）旨在量化给定饮用水供应系统中与季节性和特定位置水质问题相关的后果，以便为努力持续提升性能的小型饮用水系统提供更有效的决策依据。基于模糊规则的建模用于解决基于单一水质指南/标准测量性能时的不精确性以及小型饮用水系统运行和监测中存在的不确定性。使用从加拿大纽芬兰和拉布拉多以及魁北克的16个小型饮用水系统收集的数据对所提出的R框架进行了验证，并与加拿大环境部长理事会的水质指数（WQI）这一基于传统指南/标准的方法进行了比较。研究发现，R框架提供了更深入的水质状况，并根据故障事件的发生频率和后果更合理地对小型饮用水系统进行基准测试。
