Integrated water and sediment flow simulation and forecasting models for river reaches

被引:10
作者
Choudhury, Parthasarathi [1 ]
Sil, Briti Sundar [1 ]
机构
[1] NIT Silchar, Dept Civil Engn, Silchar 788010, Assam, India
关键词
Sediment; Water; Muskingum; Rating curve; Genetic Algorithm; Non-dominated; SOIL-EROSION MODEL; NEURAL-NETWORK; NSGA-II; PREDICTION; TRANSPORT;
D O I
10.1016/j.jhydrol.2010.02.034
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In the present study integrated water and sediment flow simulation and forecasting models for a river reach have been developed. The new models combine Muskingum model and the sediment rating model leading to integrated water discharge-sediment concentration model (WSCM) and water discharge-sediment discharge model (WSDM) for a reach. The models depict coherence in water discharge and sediment load variations at a site; incorporate two hydrologic variables, water discharge and sediment load for the gauge sites and represent revised forms of the basic Muskingum model. The models can be recast into forecasting form useful for obtaining downstream water and sediment flow forecasts Delta t' = 2kx time unit ahead. During calibration the models can select a commensurate inflow-outflow set depending on upstream and the downstream relative sediment discharge characteristics for a reach. The models can be used for developing Muskingum model for river reaches having no water discharge records. With forecasting capabilities the present models are useful in the real time management of sediment related pollution hazards in water courses. The study indicates that a single model could be used to describe both water and sediment flow in river reaches. The proposed model formulations are demonstrated for simulating and forecasting sediment concentration, sediment discharge and water discharge in the Mississippi River Basin, USA. Model parameters are estimated using non-dominated sorting Genetic Algorithm II (NSGA-II). Comparison of models performances with reported works show better performances by the present models. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:313 / 322
页数:10
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