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A Multi-Scale Analysis of Single-Unit Housing Water Demand Through Integration of Water Consumption, Land Use and Demographic Data

机译:通过耗水量,土地利用和人口数据的综合分析,对单单元房屋的需水量进行多尺度分析

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Studies evaluating the determinants of water demand typically use household-scale data or aggregated data. The household-scale data basically is preferred since it can reveal the heterogeneity in responses to the demand drivers across different consumer groups. However, the scarcity of household-scale data and its high data collection cost generally have limited the studies to rely on small samples of household data. Thus, they failed to show the spatial variation of water demand. In contrast, the aggregated studies have assessed the spatial variation of water use however they overlooked the variations across households. Using a rich source of GIS-based urban databases in Auckland, New Zealand, this study overcame this challenge by developing a large sample of 31000 single-unit housing through integration of household-level water consumption and property data with micro-scale household demographics information. This large dataset enabled this study to evaluate the water consumption both at the household scale and the census area unit scale. Panel data models were used for the water demand analysis in both scales. The proposed multi-scale analysis approach provided detailed knowledge about water consumption and its major determinants across different consumer groups and urban areas. This information may help water planners to more reliably plan water supply systems and manage consumption in the complex urban environments.
机译:评估需水决定因素的研究通常使用家庭规模数据或汇总数据。基本上首选家庭规模的数据,因为它可以揭示不同消费者群体对需求驱动因素的响应的异质性。但是,家庭规模数据的稀缺性及其高昂的数据收集成本通常限制了研究只能依靠家庭数据的小样本。因此,他们未能显示出需水量的空间变化。相反,综合研究评估了用水的空间变化,但是他们忽略了家庭之间的变化。这项研究使用了新西兰奥克兰市基于GIS的城市数据库的丰富资源,通过将家庭用水量和财产数据与微型家庭人口统计信息相集成,开发了31000套单身住房的大量样本,从而克服了这一挑战。 。庞大的数据集使这项研究能够评估家庭规模和普查区域单位规模的用水量。两种数据均使用面板数据模型进行需水分析。拟议的多尺度分析方法提供了有关不同消费群体和城市地区用水量及其主要决定因素的详细知识。这些信息可以帮助水务规划人员更可靠地规划供水系统并管理复杂城市环境中的用水量。

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