A copula-measure Me based interval multi-objective multi-stage stochastic chance-constrained programming (CMIMOMSP) model is proposed for water consumption optimization. It can conduct water allocation amid multiple users and multiple stages, and deal with the uncertainties presented as interval numbers, random fuzzy interval numbers, and stochastic variables. It improves upon multi-stage stochastic chance-constrained programming by introducing the multi-objective programming, and it can tradeoff the relationships amid economic benefit, full usage of water resources, and economic loss. It enhances the accuracy of copula function and conditional distribution function through proposing the interval functions. Besides, it can deal with the impact of the decision attitudes of managers on water allocation by formulating the function equation between water demand and the optimistic-pessimistic factor. The CMIMOMSP model is applied to a case study of the Heihe River Basin to verify its application. The results indicate that: (1) the optimistic-pessimistic factors have different degrees of positive influences on water allocation for industrial, domestic and ecological sectors; (2) the joint violated probability and optimistic-pessimistic factor have various range of impacts on agricultural water allocation; (3) tthe objective function values have different variation tendencies with the rise of joint violated probabilities and optimistic-pessimistic factors. Its robustness is enhanced by comparing it with the three single-objective programming models. The CMIMOMSP model can provide various water allocation schemes for managers with different risk attitudes in semi-arid and arid districts.

提出了一种基于copula-measure Me的区间多目标多阶段随机机会约束规划（CMIMOMSP）模型，用于优化用水量。它可以在多个用户和多个阶段之间进行水分配，并处理以区间数，随机模糊区间数和随机变量表示的不确定性。通过引入多目标规划，它改进了多阶段随机机会约束规划，并且可以在经济效益，水资源的充分利用和经济损失之间进行权衡。通过提出区间函数，它提高了copula函数和条件分布函数的准确性。除了，通过建立需水量与乐观悲观因素之间的函数方程，可以解决管理者决策态度对配水的影响。将CMIMOMSP模型应用于黑河流域的案例研究以验证其应用。结果表明：（1）乐观悲观因素对工业，家庭和生态部门的用水分配有不同程度的积极影响；（2）联合违约概率和乐观悲观因素对农业用水分配的影响范围各不相同；（3）目标函数值随着联合违规概率和乐观悲观因素的增加而具有不同的变化趋势。通过将其与三个单目标编程模型进行比较，可以增强其健壮性。