Application And Research On Real-time Flood Forecasting Model Of Reservior And Reach

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 factorsmethod 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.