Reservoirs play a major role as an essential source of surface water, especially in arid and semi-arid regions. To optimize the operation of a reservoir and determine its storage, which varies in time, the uncertainties of major influencing factors such as its inflow and evaporation should be considered. The objective of this study is to examine the effects of joint uncertainties of the inflow and evaporation of Durudzan reservoir on its performance for the first time. The Monte Carlo simulation is used for uncertainty assessment. Specifically, the monthly time series of inflow and evaporation were generated by using artificial neural networks and the standard operation policy was used for reservoir operation. Furthermore, the probabilistic distributions of four performance indices, including time-based reliability, volumetric reliability, vulnerability, and resiliency were calculated to assess the effects of the joint uncertainties of inflow and evaporation as well as the physical parameters on the reservoir variables (e.g., water release, storage, and spill). The results showed that the highest and lowest uncertainties of the reservoir water release occurred in July and May, respectively. In addition, the highest and lowest uncertainties were, respectively, observed in March and October for the reservoir storage, and in March and May for the water spill. The results also showed that the volumetric reliability had the highest uncertainty with a coefficient of variation (CV) of 0.158, while the resiliency had the lowest uncertainty with a CV of 0.020.

水库作为地表水的重要来源发挥着重要作用，尤其是在干旱和半干旱地区。为优化水库运行，确定随时间变化的水库蓄水量，应考虑入库、蒸发等主要影响因素的不确定性。本研究的目的是首次检验 Durudzan 水库流入和蒸发的联合不确定性对其性能的影响。Monte Carlo 模拟用于不确定性评估。具体而言，利用人工神经网络生成月流入和蒸发的时间序列，并采用标准作业策略进行水库作业。此外，四个性能指标的概率分布，包括基于时间的可靠性，体积可靠性，计算脆弱性和弹性以评估流入和蒸发的联合不确定性以及物理参数对水库变量（例如，水释放、储存和溢出）的影响。结果表明，水库泄水不确定性最高和最低分别出现在7月和5月。此外，最高和最低的不确定性分别出现在 3 月和 10 月的水库储存以及 3 月和 5 月的漏水。结果还表明，体积可靠性的不确定性最高，变异系数 (CV) 为 0.158，而弹性的不确定性最低，变异系数 (CV) 为 0.020。计算和恢复力以评估流入和蒸发的联合不确定性以及物理参数对水库变量（例如，水释放、储存和溢出）的影响。结果表明，水库泄水不确定性最高和最低分别出现在7月和5月。此外，最高和最低的不确定性分别出现在 3 月和 10 月的水库储存以及 3 月和 5 月的漏水。结果还表明，体积可靠性的不确定性最高，变异系数 (CV) 为 0.158，而弹性的不确定性最低，变异系数 (CV) 为 0.020。计算和恢复力以评估流入和蒸发的联合不确定性以及物理参数对水库变量（例如，水释放、储存和溢出）的影响。结果表明，水库泄水不确定性最高和最低分别出现在7月和5月。此外，最高和最低的不确定性分别出现在 3 月和 10 月的水库储存以及 3 月和 5 月的漏水。结果还表明，体积可靠性的不确定性最高，变异系数 (CV) 为 0.158，而弹性的不确定性最低，变异系数 (CV) 为 0.020。结果表明，水库泄水不确定性最高和最低分别出现在7月和5月。此外，最高和最低的不确定性分别出现在 3 月和 10 月的水库储存以及 3 月和 5 月的漏水。结果还表明，体积可靠性的不确定性最高，变异系数 (CV) 为 0.158，而弹性的不确定性最低，变异系数 (CV) 为 0.020。结果表明，水库泄水不确定性最高和最低分别出现在7月和5月。此外，最高和最低的不确定性分别出现在 3 月和 10 月的水库储存以及 3 月和 5 月的漏水。结果还表明，体积可靠性的不确定性最高，变异系数 (CV) 为 0.158，而弹性的不确定性最低，变异系数 (CV) 为 0.020。