Many Iranian metropolises, including Shiraz, are situated in arid and semi-arid regions, lacking sufficient renewable water resources. In recent years, climate changes, including drought and rising temperatures, have led to changes in water supply and demand. Given the necessity and importance of urban water supply, this study investigates the impact of different climate scenarios on residential water demand. Many studies, in their models, do not consider the social interactions between household water consumers and the change in their consumption behaviour, which serves as a fundamental drawback. Thus, the present research attempts to propose an agent-based framework by modelling social interactions via the diffusion process to investigate water consumption behaviour efficiently. The model is calibrated and applied to Shiraz City in Iran, according to the data from 2006 to 2019, and it is used to simulate each scenario for the following years until 2032. The findings show that temperature has a positive and significant effect on residential water consumption; yet, rainfall negatively affects water consumption. The simulation results of these scenarios for temperature increase or decrease and rainfall changes are estimated. In addition, the developed agent-based platform can be easily calibrated and adjusted based on the data of any other city to simulate water demand estimation under different climatic and even economic scenarios. Urban water managers can benefit from such estimates to plan future infrastructure development and proactive management of seasonal water resources under the growing pressure of potential climate change because construing the sensitivity of seasonal water consumption to climate conditions is essential to respond to variations in demand.

中文翻译：

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设计和校准基于代理的平台，以评估气候变量对住宅用水需求的影响

包括设拉子在内的伊朗许多大都市都位于干旱和半干旱地区，缺乏足够的可再生水资源。近年来，干旱和气温上升等气候变化导致水资源供需变化。鉴于城市供水的必要性和重要性，本研究调查了不同气候情景对住宅用水需求的影响。许多研究的模型没有考虑家庭用水者之间的社会互动及其消费行为的变化，这是一个根本缺陷。因此，本研究试图提出一种基于代理的框架，通过扩散过程对社会互动进行建模，以有效地调查水消耗行为。该模型经过校准并应用于伊朗设拉子市，根据2006年至2019年的数据，并用于模拟随后几年直至2032年的各个情景。研究结果表明，温度对居民用水量有显着的正向影响；然而，降雨会对用水量产生负面影响。估计这些情景对温度升高或降低以及降雨量变化的模拟结果。此外，所开发的基于代理的平台可以根据任何其他城市的数据轻松校准和调整，以模拟不同气候甚至经济情景下的需水量估算。