摘要
本文结合广西北海市南流江流域河库洪水预报问题对水库洪水预报和河段洪水预报的基本理论及模型进行了探讨。鉴于参数识别的好坏直接影响到模型的精度和效率,本文重点探讨和研究了一种高效混合遗传算法并用其来优选概念性水文模型的参数,取得了良好的效果。论文主要进行了下述工作:
一.概括了洪水预报的必要性和意义,叙述了国内外洪水预报的研究现状和发展趋势。详尽的阐述了水文预报方法的发展历史。
二.介绍了水文预报的基本概念和各种水文模型的特点。详细阐述流域水文预报产汇流模型的理论和结构以及河段洪水预报的原理和技术。叙述了洪水实时校正模型和技术。
三.对参数识别的基本方法及各种方法的特点、发展和应用情况进行了分析。介绍了遗传算法的基本概念,论述了基本遗传算法及其实现过程;鉴于基本遗传算法和传统的模型参数率定方法各有利弊,在介绍了Rosenbrock算法的基础上,将它们进行了有机的结合形成了混合遗传算法,并对遗传算子进行了设计和改进,采用了小生境技术;利用典型数学函数对混合遗传算法的性能进行了测试分析,证明了混合遗传算法与基本遗传算法相比具有更好的收敛性能和更高的收敛速度。并对多目标决策混合遗传算法进行了初步的探讨。
四.结合广西北海合浦水库的工程实例,选用西塘站以上控制面积采用新安江三水源模型对其参数进行了率定;对比分析了单目标决策的遗传算法和多目标决策的混合遗传算法的优选效果;将优选得到的参数应用于整个小江流域进行了洪水预报。在此基础上应用改进后的可变遗忘因子递推最小二乘算法对模拟结果进行了实时校正,显著提高了预报精度。最后采用三种方案进行了河库联合洪水预报,其中方案二利用分段马斯京根法和最小二乘回归方法进行河道洪水演算,计算效果较好。
The thesis studies the theory and the model of runoff forecasting and river forecasting, as well as the application in the Nanliujiang watershed. Considering the parameter estimation influencing the precision and efficiency of model directly, this thesis proposes a Hybrid Genetic Algorithm to estimate the parameter of the conceptional hydrologic model, which results show that it works efficiently and is rather satisfactory. The main content of this dissertation are as follows.1. The necessity and significance of the flood forecasting is summarized. The history of hydrology forecasting is reviewed, and the current situation and the development trend of flood forecasting in domestic and international are presented.2. The conception of hydrology forecasting and the characteristic of each model are introduced. The theory and key technology of runoff-concentration model and river flood forecasting are explained in detail. Besides, the real-time calibrating model is reviewed.3. The development, application and deficiency of the parameter estimation methods are analyzed. Following, both the basic conception of Genetic Algorithm and the Standard Genetic Algorithm are introduced. After the recommend of the Rosenbrock model, the thesis combines the GA with Rosenbrock to propose a new method called Hybrid Genetic Algorithm. The dissertation also design and improve the Genetic Algorithm operator, adopting the niche technology. The Hybrid Genetic Algorithm is evaluated by typical mathematic functions and the results prove that the Hybrid Genetic Algorithm has a stronger convergence capability and faster convergence velocity than the SGA. Moreover, the multiple-objects Hybrid Genetic Algorithm is also studied.4. Hepu reservoir in Guangxi province is taken for example. The catchment area which is located in the upstream of Xitang rainfall-station is chosen to estimate the parameter of Xin'anjiang model. The results of single-object Hybrid Genetic Algorithm and multiple-objects Hybrid Genetic Algorithm are compared. By using the estimated parameter for whole reservoir, the dissertation studies the watershed flood forecasting of Hepu. The improved recursive least-squares estimated with variable forgotten factors
method is used to improve the model efficiency evidently. Finally, three methods are used to forecast the flood of reservoir and reach respectively. With the second method, Muskingun method and least-squares regress model are used to forecast river flood, which gets the content results.
引文
[1] 张小宇.水城水库洪水预报研究.昆明理工大学硕士论文.2003(3)
[2] Division of Disaster Reduction, Office of State Flood Control and Drought Relief Headquarters, Flood Control in China (1999)
[3] 2002年北京第二届国际防洪大会(FLOOD DEFENCE'2002)
[4] 汪恕诚.资源水利的理论内涵及实践基础.中国水资源论坛.2000.4
[5] 汪恕诚.以“人与自然和谐相处”破解水的四大问题.2003
[6] 汪恕诚.再谈人与自然和谐相处.水利学会第八次全国会员代表大会.2004
[7] 吴永强.广西郁江实时洪水预报与调度系统研究.河海大学硕士论文.2003(6)
[8] Todini E and Martellied S. CLS: Constrained Linear System. 1973
[9] Todini E and Bouillot D. A Rainfall-Runoff Kalman Filter Model. In G.C.Vanteenkistred. System Simulation in Water Resources, North-Holland, Amsterdam,1975
[10] Todini E, O'Connell P E and Jones D A. Kalman Filter Estimation Problems, Real-time Hydrological Forecasting and Control. Proceedings of 1st International Workshop,1977
[11] International Association of Hydrological Sciences. Hydrological Forecasting Proceedings, Oxford Symposium. April 1980
[12] Kidanidis P K and Bras R L. Real-Time Forecasting with a Conceptual Hydrologic Model. Water Resour. Res.1980
[13] Georgakakos K P. Real-Time Flash Flood Prediction. Journal of Geophysical research,Vol.92, No,D8,Aug.20,1987
[14] 许剑华,林贞铭.短期洪水预报的变系数方程法.水文.1983
[15] 葛守西.蓄满产流模型的卡尔曼滤波算法.成都科技大学学报.1984(4)
[16] 包为民.新安江模型参数的自动率定.河海大学学报.1986
[17] 赵人俊,王佩兰.新安江模型参数的客观优选方法.河海大学学报.1989(4)
[18] 宋星原.洪水扩散波实时水位预报模型及其算法.水电能源科学.1995(4)
[19] 钟登华,王人超,皮钧.水文预报时间序列神经网络模型.水利学报.1995(2)
[20] 郭生练.水库调度综合自动化系统.武汉水利电力大学出版社.2000(4)
[21] 詹道江,叶守泽.工程水文学.中国水利水电出版社.2000(10)
[22] 张洪刚.概念性水文模型多目标参数优化技术研究.武汉大学硕士论文.2002(5)
[23] 袁作新.流域水文模型.水利电力出版社.北京.1993
[24] 长江水利委员会.水文预报方法.水利电力出版社.1990
[25] 庄一鸰,林三益.水文预报.水利电力出版社.1986
[26] 雒文生,宋星原.漳河水库上下游洪水预报方案及抗误差研究(技术报告).2003(10)
[27] 葛守西.现代洪水预报技术.中国水利水电出版社.1998
[28] 赵人俊,王佩兰.新安江模型参数的分析.水文.1988(6)
[29] 赵人俊,王佩兰.流域水文模型参数的客观优化方法.水文.1993(4)
[30] 毛文学.基因算法及其在水文模型参数优选中的应用.水文.1993(5)
[31] 谭炳卿.水文模型参数自动化优选方法的比较分析.水文.1996(5)
[32] 杨晓辉,郭菲菲.率定新安江(三水源)产汇流参数.贵州水力发电.2000(1)
[33] 张金华.模型参数识别的遗传算法优化方法及其应用.武汉大学硕士论文.2001(11)
[34] 欧春平.智能算法在流域洪水预报系统建模中的应用及其软件集成体系.大连理工大学硕士论文.2001(6)
[35] 钱镜林.现代洪水预报技术研究.浙江大学博士论文.2004(5)
[36] 吴凤燕.基于XAJ模型与MODP模型的水资源优化配置研究.武汉大学硕士论文.2003(5)
[37] Holland J H. Adaptation in Nature and Artificial Systerm. MIT Press. 1992
[38] Goldberg D E. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley. 1989
[39] 王小平,曹立明.遗传算法—理论、应用与软件实现.西安交通大学出版社.2002(1)
[40] 周明,孙树栋.遗传算法原理及应用.国防工业出版社.1996(6)
[41] 陈宝林.最优化理论与算法.清华大学出版社.1989
[42] 席少霖,赵凤治.最优化计算方法.上海科学技术出版社.1993(8)
[43] 田向荣、赵英林.遗传算法和Rosenbrock法在水文预报汇流参数优选中的比较研究.水电能源科学.2002(1)
[44] 冯尚友.水资源系统工程.湖北科学技术出版社.1990(11)
[45] 黄聪明,陈湘秀.小生境遗传算法的改进.北京理工大学学报.2004(8)
[46] 刘杰,王媛.一种高效混合遗传算法.河海大学学报.2002(3)
[47] 宋维等.一种用于多峰函数优化的改进混合遗传算法.天津师范大学学报.2003(6)