Assessing the impact of climate change on water demand is a challenging task. This paper proposes a novel methodology that quantifies this impact by establishing a link between water demand and weather based on climate change scenarios, via Coupled General Circulation Models. These models simulate the response of the global climate system to increasing greenhouse gas concentrations by reproducing atmospheric and ocean processes. In order to establish the link between water demand and weather, Random Forest models based on weather variables were used. This methodology was applied to a district metered area in Naples (Italy). Results demonstrate that the total district water demand may increase by 9–10% during the weeks with the highest temperatures. Furthermore, results show that the increase in water demand changes depending on the social characteristics of the users. The water demand of employed users with high education may increase by 13–15% when the highest temperatures occur. These increases can seriously affect the capacity and operation of existing water systems.

评估气候变化对水需求的影响是一项艰巨的任务。本文提出了一种新颖的方法，该方法通过基于耦合的一般循环模型基于气候变化情景在水需求和天气之间建立联系来量化这种影响。这些模型通过再现大气和海洋过程来模拟全球气候系统对温室气体浓度增加的响应。为了建立需水量与天气之间的联系，使用了基于天气变量的随机森林模型。该方法已应用于那不勒斯（意大利）的区域计量区域。结果表明，在温度最高的几周内，该地区的总需水量可能会增加9-10％。此外，结果表明，需水量的增加取决于用户的社会特征。气温最高时，受过高等教育的就业用户的需水量可能会增加13-15％。这些增加会严重影响现有供水系统的容量和运行。