In the hydrologic design of water management infrastructures, rainfall characteristics are often used and the available historical rainfall events in the form of intensity–duration–frequency (IDF) curves are essential. However, due to the rise in the emission of greenhouse gases, the magnitude and frequency of future extreme rainfalls will be changed. Therefore, the current study aims to develop the IDF curves models in the region of Makkah Al Mukarramah, Saudi Arabia. In this study, five models were developed to estimate the rainfall intensity for the different durations and return periods, using three statistical parameters e, m, and C, calculated from the rainfall intensity data for the time series in each station. The results showed that the rainfall intensity average is ranged between 15.4 mm/10 min and 25.9 mm/60 min for Al Karr Sufli station from 1966 to 2005, and 29.8 mm/120 min and 49.6 mm/720 min for Baqrane station during the period of 1971–2005. Besides, the KGE, R², and Theil’s U performance tests of the probability distribution models revealed that the exponential model is the best for the Al-Barzah, Ain Al Azizia and Al Karr Sufli, and Humma Syssed stations, and the log Pearson III model is the best model for Baqrane station. The outcomes of this research reveal the potential of this approach in projecting upcoming climate situations for urban catchment where long-term hourly rainfall data are not easily available.

在水管理基础设施的水文设计中，经常使用降雨特征，并且以强度-持续时间-频率（IDF）曲线形式出现的可用历史降雨事件至关重要。但是，由于温室气体排放量的增加，未来极端降雨的数量和频率将发生变化。因此，当前的研究旨在在沙特阿拉伯的麦加·穆卡拉玛地区开发IDF曲线模型。在这项研究中，使用三个统计参数e，m和C，开发了五个模型来估计不同持续时间和返回期的降雨强度，这三个统计参数是根据每个站的时间序列的降雨强度数据计算得出的。结果表明，平均降雨强度在15.4 mm / 10 min和25之间。1966年至2005年，Al Karr Sufli站为9毫米/ 60分钟，1971年至2005年期间，Baqrane站为29.8毫米/ 120分钟和49.6毫米/ 720分钟。此外，KGER ²和Theil对概率分布模型的U性能测试表明，指数模型最适合Al-Barzah，Ain Al Azizia和Al Karr Sufli和Humma Syssed测站，对数Pearson III模型是最佳模型前往Baqrane站。这项研究的结果揭示了该方法在预测长期集约降雨数据不易获得的城市集水区未来气候状况时的潜力。