中文摘要：

灌区多水源灌溉系统中存在许多不确定性因素,随着系统环境的变化及不确定性因素的影响,导致其配水过程具有动态特征。针对灌区多水源灌溉系统的配水特点,该文建立基于区间多阶段随机规划的灌区多水源优化配置模型。同时,考虑灌溉水对作物产量的影响,引入水分敏感指数权重系数,并以黑龙江省和平灌区水稻不同生育阶段灌溉水资源优化配置进行实例研究。结果表明,在不同来水情境下,管理者可根据各个生育阶段水分敏感指数权重系数,判断作物不同生育阶段的需水敏感程度,当来水情境的来水量多时,会产生余水量,可调配给下一生育阶段;当来水情境的来水量少时,管理者可在减少灌溉水量与增加外调水之间进行权衡,并根据需水关键期与需水非关键期做出决策,使水资源在作物生育阶段间及作物生育阶段内进行分配,实现灌区多水源灌溉系统的动态配水。该模型的应用在确保作物产量的同时,使灌溉水资源在作物各个生育阶段进行合理配置,有效地避免了水资源浪费,对提高灌溉水利用效率、保证水资源的可持续利用具有重要意义。

英文摘要：

There are many uncertain factors in the multi-source water irrigation system, along with the changes in the system environment and the effects of uncertainty, leading to dynamic characteristics of the water distribution process.Based on the water distribution characteristics of irrigation system, interval-parameter multi-stage stochastic programming model was constructed and improved to consider effect of sensitive index of various stages and water irrigation on crop production, which introduced water sensitivity index weights and made a case study over rice at different growth stages in Heping irrigation area. The study area of this paper had two water sources： the surface water and the ground water, which also could be divided into three different projects by the water intake mode： water diversion project, water lifting project and well irrigation project. At the same time, Liuhe reservoir was taken as a water external source, where all the water system constituted a complex multi-water source supply system. In this study, four stages of rice growth were selected as the research period, i.e. tillering stage, jointing stage, heading stage and milk stage. The water sensitive index weight coefficients in each growth stage were 0.37, 0.46, 0.11 and 0.06 respectively. Inflow level of different growing stage was random variables and closely related to hydrological factors such as rainfall and runoff, hence the probability density function was introduced to represent uncertainty, and discrete interval was used to show other hydrologic and economic uncertainty. Multi-stage stochastic programming model could allocate water between different phases and different growing stages under a series of inflow level. Because of the uncertainty of inflow water, a four-period（five-stage） scenario tree and improved interval-parameter multi-stage stochastic programming model were used to carry out dynamic distribution of water in multiple stages of growth. Research results showed that in the context of different inflow level,