The importance of freshwater for human societies and sustainable urban development is paramount. This study presents a new approach and framework for spatial modelling of urban drinking water consumption patterns (UDWCP) in light of a drinking water sustainability assessment. The approach was developed based on the GIS multi-criteria decision analysis (MCDA) and its efficiency was evaluated for spatial UDWPC mapping in Tabriz city, Iran. To achieve this goal, we identified the main water consumption indicators (WCI) (e.g. urban fields, population, land use/cover and their related sub-spatial factors), and determined their significance using the analytical network process. In addition, the sensitivity and uncertainty analyses was applied to reduce the inherent error in criteria weights. A GIS-based aggregation function was applied to discern the UDWCP map. Finally, regression analysis was used to determine the spatial correlation of the water consumption with different urban fields as well as the ratio of each WCI for the sustainability assessment objects were computed. According to results, urban fields, texture and demographic properties have a significant impact on the water consumption ratio. In the context of the urban texture, this study revealed that water consumption rates in both run-down and slums/informal settlements are relatively high. Results of this research provide a comprehensive understanding of UDWCP and their contribution to urban water consumption in Tabriz city. The importance of fresh water for human societies and the numerous issues related to water scarcity around the world is undisputed, and our proposed approach can be employed to efficiently model UDWCP and provide critical information for decision-makers and authorities worldwide to assist with the sustainable development of urban environments.

淡水对人类社会和可持续城市发展的重要性至关重要。根据饮用水可持续性评估，本研究为城市饮用水消费模式（UDWCP）的空间建模提供了一种新的方法和框架。该方法是基于GIS多标准决策分析（MCDA）开发的，并针对伊朗大不里士市的空间UDWPC制图评估了其效率。为了实现这一目标，我们确定了主要用水指标（WCI）（例如，城市田地，人口，土地利用/覆盖及其相关的子空间因素），并使用分析网络过程确定了它们的重要性。此外，还进行了敏感性和不确定性分析，以减少标准权重中的固有误差。应用基于GIS的聚合功能来识别UDWCP地图。最后，使用回归分析来确定不同城市区域用水量的空间相关性，并计算可持续性评估对象的每个WCI的比率。根据结果​​，城市田地，质地和人口统计学特征对耗水率有重大影响。在城市纹理的背景下，这项研究表明，流失地区和贫民窟/非正式住区的耗水率都很高。这项研究的结果提供了对UDWCP及其对大不里士市城市用水的贡献的全面理解。淡水对人类社会的重要性以及与世界各地水资源短缺有关的众多问题是无可争议的，