부산대학교 도서관

Water is a finite resource. Increasing population, rapid urbanization, and climate change incidents are continuously adding pressure on freshwater supplies. Overcoming these issues require change in current urban water management (UWM) strategy. In this study, a conceptual model of One Water Community has been developed that aims to reduce potable water use (R PWU) using One Water Approach (OWA). Based on OWA's six guiding principles, five interventions (i.e., control factors) and sixteen parameters have been identified. Each parameter is simulated twice by running 10,000 iterations to calculate a percentage reduction of potable water use at 90th, 50th, and 10th percentiles. A Taguchi-based optimization method has been used to determine the optimum combination of parameters from each of the five control factors [water saving appliances (WSA), reclaimed water use (RWU), resource recovery (RR), low impact development (LID), and good governance (GG)]. L 16 orthogonal array experimental design plan was considered in conducting the trials. ANOVA analysis showed that RWU, RR, and WSA were the most influential factors on R PWU performance at 90th, 50th, and 10th percentiles. Validation tests validated the model by predicting the S/N ratio at the optimum condition. The findings indicated that water sense labeled urinals, reclaimed water for agriculture purposes, emissions reductions from treatment plants, bioswales, and increased public awareness were the most optimum parameters in achieving the highest potable water reduction potential at the 90th percentile. The developed model will open new avenues in UWM, which will assist decision-makers in building sustainable, reliable, and resilient urban water systems. [Display omitted] • One Water Approach concept is capable to bring a change in urban water management. • A conceptual model of One Water Community was developed based on six principles. • Five factors and sixteen parameters were identified to reduce potable water use. • A Taguchi based technique was employed to determine optimum parameters combination. • Experimental values were greater than predicted values to justify the optimum condition established in the study. [ABSTRACT FROM AUTHOR]