Residential Water Consumption Modeling in the Integrated Urban Metabolism Analysis Tool (IUMAT)

This paper details a method for residential water consumption modeling within the Integrated Urban Metabolism Analysis Tool (IUMAT), a computational modeling platform for evaluating environmental performance of urban communities under alternative growth scenarios. A bottom-up approach is introduced to generate end-use indoor and outdoor water profiles by applying GLM and Ridge regression methods to Residential End Uses of Water, Version 2 (REU II-2016) dataset and investigating the influence of demographic and climate factors, as well as utility rate structures on patterns of consumption. The data is collected from 2010 through 2013 by nine utilities that operate in North America on 771 and 838 single family units for indoor and outdoor water use respectively. Potential advances to surveying methods as well as the need for tools that allow simultaneous, isolated assessment of educational and technological conservation measures are explained.

本文详细介绍了一种在城市综合代谢分析工具（IUMAT）中建立住宅用水模型的方法，IUMAT是一个用于评估不同增长情景下城市社区环境绩效的计算建模平台。引入了一种自下而上的方法，通过将广义线性模型（GLM）和岭回归方法应用于《住宅用水终端用途第2版》（REU II - 2016）数据集，并研究人口统计学和气候因素以及水电费结构对用水模式的影响，来生成终端用途的室内和室外用水概况。这些数据是由在北美运营的9家公用事业公司在2010年至2013年期间分别从771个和838个单户住宅单元收集的室内和室外用水数据。文中还阐述了调查方法可能的改进以及对能够同时、独立评估教育和技术节水措施的工具的需求。