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Forecast Of Inflow Hydrograph And Out Flow Sediment Concentration Of Reservoir

Posted on:2004-01-24Degree:MasterType:Thesis
Country:ChinaCandidate:Y J LiFull Text:PDF
GTID:2132360092481389Subject:Environmental Engineering
Abstract/Summary:PDF Full Text Request
Dameges of flood are always severe in China in all ages, deposition of sediment in reservoir are serious in Loess Plateau, too. So forecast of inflow hydrograph and out flow sediment concentration of reservoir are very important.According to the characteristics of Heihe watershed, flood hydrograph into Jinpen reservoir is studied. At the same time, prediction of outflow sediment concentration of Feng Jia Shan reservoir is modeled too. The objective is to get more exactly prediction of flood hydrograph and sediment concentration profile based on measured data. The main contents and results of this paper are as follows:1. Considering the characteristics of Heihe watershed that has smaller area and belongs to semi-humid region, Xinanjiang Model is adopted to predict inflow of Jinpen reservoir and the results are satisfied.2. P~Pa~R Correlation Diagram is adopted to calculate net rain, then the response function model is used to predict flood hydrograph, the results are not as good as those of Xinanjiang Model.3.With the input of duration rainfall series before current time, BP ANN model with one hidden layer is tried to predict flood. The results are good for the training data set, but generalisation is weaker.4.The input is the same as that of BP model, weights with the same value of dimensionless unit hydrograph are been added to RBF ANN model between input layer and hidden layer to predict flood. The results are good in the training data set, but generalisation is weaker.5.Traditional hydrologic models are compared with ANN models in floodprediction, avail of every model and cause of weaker generalisation of ANN is analyzed, at the same time advices on improving ANN in flood prediction are proposed.6. RBF model is tried to predict outflow sediment concentration of Feng Jia Shan reservoir. Based on time of flood entering reservoir and the time of opening brake, the network structure is chosen. The results are good.
Keywords/Search Tags:flood prediction, prediction of outflow sediment concentration, hydrologic model, artificial neural networks
PDF Full Text Request
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