【作者】 李建柱；

【导师】 冯平；

【作者基本信息】 天津大学 ， 水文学及水资源， 2008， 博士

【摘要】 流域水文模型是洪水预报的主要工具,是减免洪水损失非常重要的非工程措施,也是合理利用水能、水资源的非工程措施。无论是重大问题的决策、水利工程的运行,还是防洪抗旱等均离不开水文模型的支撑。在我国半干旱半湿润地区,现有的水文模型难以取得比较满意的结果。本文选择半干旱半湿润典型代表区海河流域为研究对象,通过对流域降雨径流响应的分析,初步确定了流域的产汇流机制以及影响产汇流参数的因素,据此建立了流域产汇流模型,并对模型进行了参数率定和验证。模型在海河流域下垫面变化对洪水径流的影响分析中得到了应用。主要研究成果如下:(1)通过分析流域径流对降雨的响应,认为流域的产流机制并非单一,而是与降雨特性和初始土壤含水量有关,如果降雨强度较小、初始土壤含水量高,以蓄满产流方式为主;降雨强度大、初始土壤含水量低,以超渗产流方式为主。结合土壤的大孔隙下渗原理建立了流域大孔隙超渗和大孔隙蓄满产汇流模型,在柳河流域和紫荆关流域得到了验证。(2)汇流单位线决定了径流模拟的精度,采用实测降雨径流资料,通过基流分割和净雨计算来推求的单位线,由于暴雨量级和暴雨中心位置不同,单位线的形状也不同。SCS无因次单位线和由概率密度函数推求的单位线在无资料地区是一种有效的汇流计算途径。(3)为了提高模型参数率定的效率,对模型中的参数采用RSA和Sobol’两种全局灵敏度分析方法进行了参数灵敏度分析,两种方法在确定性系数、径流总量误差、相关系数和均方差等不同的目标函数控制条件下所得的结果基本一致。这样,对模型中较为敏感的参数进行率定,不敏感的参数采用经验值即可。RSA法率定的参数不是一个最优值,而是对参数值一个较小范围的确定,避免了参数的局部最优解。(4)选择下垫面变化较大的海河流域为研究对象,分析了其子流域柳河流域和紫荆关流域的下垫面变化对产汇流因子的影响。在柳河流域和紫荆关流域分别率定了大孔隙蓄满产汇流模型和大孔隙超渗产汇流模型在80年代前和90年代后的两组参数,用这两组参数分别模拟历史洪水。结果表明,由于下垫面的变化,相同降雨情况下90年代后的洪峰流量和洪水总量比80年代前有所减小,在柳河流域分别平均减少4.9%和1.7%,在紫荆关流域分别平均减少4.8%和1.7%。更多还原

【Abstract】 Hydrological model is an effective tool for flood prediction, a very important non-project measure for flood loss reduction, and for reasonable water resources utilization. So we need the support of hydrological model in decision-making, run of the hydraulic engineering, and flood control and so on.The simulated flood results by any hydrological model are not good in semi-arid and semi-humid areas. In this paper, Haihe river basin which is a typical semi-arid and semi-humid watershed in China is selected. Runoff response to rainfall is analyzed to understand the runoff generation mechanisms in the basin and to research the influential parameters on runoff generation. Thereby, two runoff generation models considering macropore flow are established and applied in Haihe river basin to search the effects of land use/land cover change on flood. The main results are as follows.(1) Runoff response to rainfall is analyzed, and the results are found that not a single runoff generation mechanism exists in the basin, but relates to the rainfall characteristics and the initial soil moisture. If the rainfall intensity is low and the initial soil moisture is high, saturation-excess runoff is dominant; if the rainfall intensity is high and initial soil moisture is low, infiltration-excess runoff is dominant. Thereby, taking soil macropore into consideration, infiltration-excess runoff generation model and saturation-excess runoff model are established and calibrated in Liuhe and Zijingguan basin.(2) The simulation precision depends on unit hydrograph. The unit hydrographs obtained from observed rainfall and runoff data are different if the rainfall is of different amount, intensity and center. SCS dimensionless unit hydrograph and unit hydrographs derived by probability distributions are a feasible way in the areas without data.(3) Two global sensitivity analysis methods, RSA(Regional sensitivity analysis) and Sobol’methods, are adopted to improve model calibration efficiency. The results of the study show that model parameter sensitivities are not impacted by the selection of analysis method, as well as objective functions, but a little difference in different basins. So, in the process of parameter calibration, only the sensitive parameters are calibrated, and the values of non-sensitive parameters are made by experience. The results of RSA method are not single values, but a narrow range. (4) Land use/land cover change can affect the flood frequency. Two sub-basins of Haihe river basin are selected and the change in trend of runoff generation and flow routing parameters are made analysis to confirm the effect of land use/land cover change on flood. We use the rainfall and runoff data before 1980 and after 1990 to calibrate the models, and obtained two different series of parameters. And then, the two series of parameters are used to simulate all the floods in order to make comparisons. The results show that the peak flow and flood volume all decreased after 1990, and in Liuhe basin, they decreased by 4.9% and 1.7% respectively, and in Zijingguan basin 4.8% and 1.7% respectively.更多还原