【作者】 吴新；

【导师】 黄强；

【作者基本信息】 西安理工大学 ， 水文学及水资源， 2006， 博士

【副题名】以南水北调西线工程为例

【摘要】 跨流域调水是解决水资源时空分布不合理的有力措施。跨流域调水是结构复杂、形式多样涉及多水源、多目标、高维、跨学科、复杂的系统工程问题。由于跨流域调水的复杂性、涉及问题的多样性以及跨流域调水工程的具体情况千变万化,使得目前跨流域调水理论研究尚不完善。本文针对南水北调西线工程,以随机动态的观点,对南水北调西线跨流域调水系统中的缺水-输水-配水环节进行深入研究,探索在这一领域尚未被充分研究,而对工程规划、决策很重要的相关理论、方法和模型。本研究不仅对南水北调西线跨流域调水工程的规划论证有参考价值和指导意义,而且对其它跨流域调水项目的规划、设计和管理运行也有重要参考价值。论文结合南水北调西线工程,在分析黄河干流径流特性和各种影响因素的基础上,对缺水-输水-配水环节涉及到的理论、方法和模型进行了研究,从而为南水北调西线工程的规划论证提供理论基础。论文的主要研究内容和取得的成果有以下几个方面:(1)提出了黄河干流各节点水文缺水分类预测和决策树模型,在此基础上,进一步推求了黄河干流各节点水文缺水状态转移概率矩阵。水文缺水分类预测和决策树模型基于数据挖掘和信息论方法,模型不仅可以用于计算各节点来水频率的动态水文缺水量,而且还可以对各节点未来的水文缺水状态进行识别、分类和预测。黄河干流节点水文缺水分类预测和决策树模型,是黄河干流早期干旱预警系统的重要组成部分。(2)用时间序列理论证明了黄河干流节点水文缺水状态转移序列的平稳性,并实现了对节点水文缺水状态的分步预测。通过推求水文缺水状态的n步转移概率矩阵,分析得到了未来不同状态水文缺水的概率分布。时间序列理论也是预测未来水文缺水状态的有力工具,它可为南水北调西线工程调水规模的决策提供理论基础。(3)对南水北调西线工程输水环节,以前的文献较少提及。本文针对黄河干流输水能力的种种限制因素进行分析,得到了满足各种限制条件下,西线可能最大调水量,可以给工程规划、决策提供参考依据。(4)用Poisson过程推测了南水北调西线工程未来不同使用强度的概率分布情况,可供西线工程规划、设计和管理参考。(5)建立了基于概率的配水模型,并用鞅解决了复杂的概率模型计算的问题。配水模型涉及到复杂的条件概率计算问题,传统的概率统计算法无法胜任多维、随机、动态的配水模型计算,本研究引用随机过程理论中的鞅,解决了高维随机配水模型的计算。该模型虽然只能解决部分满足一定条件的节点配水问题,但模型在求解过程中引用的鞅,为其它类似问题的求解提供了一个有益的探索。(6)用序列运算理论,得到了南水北调西线工程在三个随机过程共同作用下的合理调水量,可以为南水北调西线工程调水规模决策、论证提供重要理论依据。(7)建立了古典多维尺度(CMDS)配水模型。CMDS配水模型是一个实时、多维、动态随机模型,它是传统一维配水模型的重要突破。该模型较好地解决了水资源实时动态随机配置问题,能有效防止枯水年和平水年黄河流域水资源配置不当,造成的下游断流问题。CMDS配水模型还是MDS模型传统应用领域的重要拓展。CMDS配水模型的多维性、实时性和随机性,可以实现黄河干流节点径流实时配置。该模型具有灵活性和数据输入的方便性,有广阔的拓展空间,可以适应大型流域复杂的配水问题。更多还原

【Abstract】 Interbasin water transfer (IWT) was important way to deal with water resources spatial allocation unadapted. IWT was complex and high dimensional system problem. Up till now, the theory of IWT was imperfect. The paper focus on South-North water transfer western route (SNWTWR) planning, making further study of water shortage, water transfer and water allocation. It presented a new approaching to planning, designing and managements IWT. The main research content and results are as follows:(1) Water shortage classification and decision tree models were presented. Further more, the matrix of probability change water shortage situation was deduced. It was been used to prediction of node’s water shortage situation. The quantity and located water shortage were been calculated. The research expands using of classification model.(2) Based on the time series theory, Yellow River node’s hydrology water shortage situation series stationary was been proved. Further more, n steps probability change matrix water shortage situation was also deduced. It was successful predicted node’s further hydrology water shortage situations.(3) Limited water transfer ability of Yellow River main channel was considered. Only few attempts have so far been made at water transfer ability of Yellow River. It was important to SNWTWR planning. Under these limited, the maximal water quantity of SNWTWR’s was calculated.(4) Poisson process was been used to estimated SNWTWR’s bring probability to bear operation. It was useful to support the SNWTWR project decision.(5) The stochastic water allocation model also been presented. It was only partly using in water allocation, but it first imply the martingales process in solving stochastic model. It was a new approaching in stochastic model.(6) Sequence Operation Theory was been used to choice quantity of water transfer of SNWTWR. It was been deduced under multiprocessing of stochastic. It was given a theory support for choice quantity of water transfer of SNWTWR.(7) The paper develops a new water allocation model approach that three variables take into consideration. The traditional model only can consider the one variable that is water quantity. It was a breakthrough of water allocation model. In larger scale catchments, water users scatter different position. These are runoff join the main channel along with river. These kinds of situation makes one dimension model can not be used. The new water allocation model was presented. The model based on the Multidimensional Scaling (MDS) which a nonparametric technique is used. It was imply spatial reconstruction to map the high dimension coordinate to the 2D or 3D. So that, MDS water allocation model can introduced position coordinates to represent scatter uses, node runoff to represent water quantity that be distributed and probability to represent the node water requirement. A sample have eight node Yellow River water allocation was presented. The calculated outcome show that it was good fitting with the real situation.更多还原