查看更多>>摘要：A parameterized expression for sand wave morphology in rivers is established using a flow resistance law while accounting for sediment incipient velocity.A distinct relation is drawn between the proposed characteristic parameters and the sand wave morphology based on flume data.Support vector machines(SVMs)are then used to separate the boundaries of the sand wave morphology due to the high classification accuracy of SVMs.The boundary line data from each sand wave morphology is extracted and fitted to establish a discriminant standard,which is then successfully validated using experimental and quantifiable data.Also,based on the foregoing methodoly,it is further discovered that the short-term significant fluctuation of sand wave morphology is closely correlated with significant channel changes in rivers with a high width-depth ratio,using Yellow River Estuary as an example.
查看更多>>摘要：Soil loss management requires reliable data for assessing the conditions prevailing in a watershed.Suspended sediment concentration(SSC)is one of the indicators of soil loss,and its data and asso-ciated properties are essential for integrated watershed management.However,until now,practical methods for estimating the temporal variation of SSC at the watershed scale,i.e.,a sediment graph(SG),using measured data have been given less attention.Therefore,the current study was planned to simulate the SG through conceptual modeling of the soil erosion process and sediment yield.The Galazchai Watershed in West Azerbaijan Province,Iran,was selected as a case study.In this regard,the isochrone histograms were initially prepared using two methods of the longitudinal channel profile and spatially distributed travel time.Soil erosion was calculated in each isochrone segment using the Revised Universal Soil Loss Equation(RUSLE),applying the lumped and cellular automata approach.The soil erosion between isochrones was subsequently routed using the Hadley,WaTEM/SEDEM,and newly modified U.S.Forest Service methods.The last method was developed based on seven stan-dardized variables for the current research.Synthetic SGs were ultimately derived from 12 different combinations of the study methods.The modeling performance was assessed using 38 storm events collected over several years.The base time,time to peak,peak value,and total sediment load of the simulated and observed SGs were evaluated using relative error.Comparison based on the evaluation indicators indicated better performance of the combination of the spatially distributed travel time method,cellular automata,and modified U.S.Forest Service method with the coefficient of efficiency and the normalized coefficient of efficiency varying from-1.16 to 0.99 and from 0.32 to 0.99 for the calibration and validation stages,respectively.However,none of the models were simulating satis-factorily the entire sediment graphs.
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