首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Prediction of sedimentation in reservoirs by combining catchment based model and stream based model with limited data
Authors:Abebe Tadesse  Wenhong Dai
Institution:Hohai University, Department of Water Conservancy and Hydropower Engineering, Nanjing 210098, China
Abstract:Estimation of sedimentation in reservoirs helps in the management and design of the reservoir's useful capacity. This research was done on the Awash River basin at the Koka Dam Reservoir in Ethiopia. The method applied was the loose integration of the Soil and Water Assessment Tool(SWAT) model and Hydrologic Engineering Center-River Analysis System(HEC-RAS) model for the estimation of the sediment load reaching the reservoir. The SWAT model was used for the estimation of erosion at the catchment level,and the HEC-RAS model was applied to estimate the sediment transport in the river channel. The implemented method allows sedimentation in the floodplains and bed shear stress to be considered in the sediment modeling, which cannot be considered in the SWAT model. In addition, the river cross sectional properties and the hydrodynamic processes in the rivers were considered in the modeling process. The data used in this study are a combination of i) observed data collected by government agencies, ii) data available online in data repositories, and iii) data extracted from remote sensing in the Shuttle Radar Topographic Mission(SRTM) Digital Elevation Model(DEM). The calibration and validation of the SWAT model was done by using Sequential Uncertainty Fitting(SUIF-2) calibration and validation tools. The HEC-RAS model was calibrated by adjusting the roughness factor. The output from the integrated approaches gives better estimates of flow and sediment near the inlet to the reservoir, with coefficients of determination of 0.85 and 0.67, respectively, and Nash Sutcliffe coefficients of model fit efficiency of 0.90 and 0.62, respectively, for daily simulations.
Keywords:Awash River  SWAT  HEC-RAS  Rating curve
本文献已被 维普 万方数据 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号