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ASSESSMENT OF BED-LOAD PREDICTORS BASED ON SAMPLING IN A GRAVEL BED RIVER

Journal of Hydrodynamics 2012年第1期24卷 145-151页

作者： haddadchi arman OMID Mohammad H. DEHGHANI Amir A. School of Environment Griffith UniversityNathanQld 4111Australia Department of Irrigation and Reclamation Engineering University of TehranTehranIran Department of Irrigation Engineering Golestan Agriculture and Natural Resources UniversityGorganIran

Bedload transport in alluvial channels has been extensively studied and different equations based on field and/or experimental data have been *** of bed-load transport rate using different equations results in wide ranges which are not always *** this study,some of the universal bedload predictors were evaluated with measured load by a Helley-Smith sampler in the Node River,a gravel bed river in the northeast part of *** 19 sets of data,14 series of data were used to evaluate the bed-load transport *** results show that the equations presented by Van Rijn,Meyer-Peter and Mueller,and Ackers and White may adequately predict bedload transport in the range of field data.

关键词： bedload transport gravel bed river bed-load sampling Gorgan-Iran

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Total load transport in gravel bed and sand bed rivers case study:Chelichay watershed

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International Journal of Sediment Research 2013年第1期28卷 46-57页

作者： arman haddadchi Mohammad H.OMID Amir A.SDEHGHANI School of Environmental and Rural Science University of New England Dept.of Irrigation and Reclamation Engineering University of Tehran

Field experiments were conducted on total load transport in the Chelichay River Basin,a mountainous catchment （1,400 km;） located in north eastern of Iran,to evaluate total load formulas including four gravel bed rivers and a sand bed river（Qaresoo River）.Gravel bed rivers in Chelichay River Basin can be grouped into two types;steep slope rivers with high shear values（Chehelchay River and Khormaloo River） and mild slope rivers with low shear values（Narmab River and Soosara River）.Two depth integrating suspended load samplers（DH-48 and D-49）,and two bed load samplers（Helley-Smith and BLSH） were used to measure total *** performance is tested of 8 total load transport formulae including 4 macroscopic and 4 microscopic methods.A systematic and thorough analysis of 59 sets of data collected from sand bed river indicate that Yang and Engelund and Hansen reach to the better results, and from four gravel bed rivers confirmed that the methods of Karim and Kennedy and Engelund and Hansen yields the best results for steep slope rivers,and the methods of Einstein and Bijker are ranked highest in gradual slope rivers.

关键词： Sediment Total Load Gravel Sampling

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Sediment fingerprinting in fluvial systems:review of tracers,sediment sources and mixing models

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International Journal of Sediment Research 2013年第4期28卷 560-578页

作者： arman haddadchi Darren S.RYDER Olivier EVRARD Jon OLLEY Australian Rivers Institute Griffith University School of Environmental and Rural Sciences University of New England Laboratoire des Sciences du Climat et de l'Environnement(LSCE/IPSL)

Suspended sediments in fluvial systems originate from a myriad of diffuse and point sources,with the relative contribution from each source varying over time and *** process of sediment fingerprinting focuses on developing methods that enable discrete sediment sources to be identified from a composite sample of suspended *** review identifies existing methodological steps for sediment fingerprinting including fluvial and source sampling,and critically compares biogeochcmical and physical tracers used in fingerprinting *** of applying different mixing models to the same source data are explored using data from 41 catchments across Europe,Africa,Australia,Asia,and North and South *** application of seven commonly used mixing models to two case studies from the US(North Fork Broad River watershed) and France(BIcone watershed) with local and global(genetic algorithm) optimization methods identified all outputs remained in the acceptable range of error defined by the original *** propose future sediment fingerprinting studies use models that combine the best explanatory parameters provided by the modified Collins(using correction factors) and Hughes(relying on iterations involving all data,and not only their mean values) models with optimization using genetic algorithms to best predict the relative contribution of sediment sources to fluvial systems.

关键词： watershed fluvial sampling source tracing modeling local optimization genetic algorithm

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Evaluation of suspended load transport rate using transport formulas and arti- ficial neural network models (Case study: Chelchay Catchment)

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Journal of Hydrodynamics 2013年第3期25卷 459-470页

作者： haddadchi arman MOVAHEDI Neshat VAHIDI Elham OMID Mohammad Hossein DEHGHANI Amir Ahmad Australian Rivers Institute Griffith University Nathan QLD 4111 Australia Department of Water Engineering Gorgan University of Agricultural Sciences and Natural Resources GorganIran Department of Irrigation and Reclamation Engineering University of Tehran Karaj Iran

Accurate estimation of sediment load or transport rate is very important to a wide range of water resources projects. This study was undertaken to determine the most appropriate model to predict suspended load in the Chelehay Watershed, northeast of Iran. In total, 59 data series were collected from four gravel bed-rivers and a sand bed river and two depth integrating suspended load samplers to evaluate nine suspended load formulas and feed forward backpropagation Artificial Neural Network （ANN） structures. Although the Chang formula with higher correlation coefficient （r = 0.69） and lower Root Mean Square Error （RMSE = 0.013） is the best suspended load predictor among the nine studied formulas, the ANN models significantly outperform traditional suspended load formulas and show their superior performance for all statistical parameters. Among different ANN structures two models inclu- ding 4 inputs, 4 hidden and one output neurons, and 4 inputs, 4 and one hidden and one output neurons provide the best simulation with the RMSE values of 0.0009 and 0.001, respectively.

关键词： sediment transport suspended load formulas Artificial Neural Network (ANN) river engineering

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