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Готові списки джерел за темами / Bedload predictor

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Добірка наукової літератури з теми "Bedload predictor"

Автор: Grafiati

Опубліковано: 11 березня 2023

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Статті в журналах з теми "Bedload predictor"

1

Gilja, Gordon, and Neven Kuspilić. "Dune geometry estimation using apparent bedload velocity as predictor variable." E3S Web of Conferences 40 (2018): 02054. http://dx.doi.org/10.1051/e3sconf/20184002054.

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Dune formation in river systems influences sediment transport, flow characteristics, bank erosion, flood control, navigation and the protection of land and infrastructure. Research on dunes is mainly flume-based, and conclusions from such research are rarely, if at all, verified with field measurements. Dune formation and geometry in terms of height, length and steepness is most commonly correlated with averaged flow parameters as flow depth. Application of relations defined in flume conditions is limited due to stationary flow conditions and extrapolation issues for natural watercourses. It i

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2

Badoux, A., J. M. Turowski, L. Mao, N. Mathys, and D. Rickenmann. "Rainfall intensity–duration thresholds for bedload transport initiation in small Alpine watersheds." Natural Hazards and Earth System Sciences 12, no. 10 (2012): 3091–108. http://dx.doi.org/10.5194/nhess-12-3091-2012.

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Abstract. Although channel discharge represents one of the primary controls of bedload transport rates in mountain streams, it is rarely measured in small, steep catchments. Thus, it is often impossible to use it as a predictor of hazardous bedload events. In this study, the characteristics of rainfall events leading to bedload transport were investigated in five small Alpine catchments located in different geographical and morphological regions of Switzerland, Italy and France. Using rainfall data at high temporal resolution, a total of 370 rainfall events were identified that led to abundant

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3

Kleinhans, M. G., A. W. E. Wilbers, and W. B. M. ten Brinke. "Opposite hysteresis of sand and gravel transport upstream and downstream of a bifurcation during a flood in the River Rhine, the Netherlands." Netherlands Journal of Geosciences 86, no. 3 (2007): 273–85. http://dx.doi.org/10.1017/s0016774600077854.

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AbstractAt river bifurcations water and sediment is divided among the downstream branches. Prediction of the sediment transport rate and division thereof at bifurcations is of utmost importance for understanding the evolution of the bifurcates for short-term management purposes and for long-term fluvial plain development. However, measured sediment transports in rivers rarely show a uniquely determined relation with hydrodynamic parameters. Commonly a hysteresis is observed of transport rate as a function of discharge or shear stress which cannot be explained with the standard sediment transpo

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4

Zhang, Bin, Xing Nian Liu, and Feng Guang Yang. "Two Stochastic Fraction Bedload Transport Rate Models for Nonuniform Sediment." Applied Mechanics and Materials 295-298 (February 2013): 1894–97. http://dx.doi.org/10.4028/www.scientific.net/amm.295-298.1894.

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Based on a method stochastic processes, two new bedload transport models for the ith size fraction nonuniform sediment are theoretically developed by using a stochastic model of sediment exchange and the probabilistic distribution of fractional bedload transport rates. The relations, proposed recently by Yang, for the probability of fractional incipient motion and for the average velocity of particle motion are introduced to bedload formulas. Plenty of experimental data for the bedload transport rate of uniform sediment are used to determine parameters. Finally, the two models are verified wit

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5

Roushangar, Kiyoumars, and Roghayeh Ghasempour. "Prediction of non-cohesive sediment transport in circular channels in deposition and limit of deposition states using SVM." Water Supply 17, no. 2 (2016): 537–51. http://dx.doi.org/10.2166/ws.2016.153.

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Sedimentation in sewer pipes has a negative impact on the performance of sewerage systems. However, due to the complex nature of sedimentation, determining the governing equations is difficult and the results of the available classic models for computing bedload transport rate often differ from each other. This paper focuses on the capability of a support vector machine (SVM) as a meta-model approach for predicting bedload transport in pipes. The method was applied for the deposition and limit of deposition states of sediment transport. Two different scenarios were proposed: in Scenario 1, the

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6

Bayram, Atilla, Sean O'Neil, and Yang Zhang. "SEDIMENT TRANSPORT FIELD DATA AND NUMERICAL MODELING STUDY TO SUPPORT DREDGE PIT INFILL RATE ESTIMATES." Coastal Engineering Proceedings, no. 36v (December 31, 2020): 57. http://dx.doi.org/10.9753/icce.v36v.papers.57.

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Site specific bedload and suspended sediment transport data collected at two test pit locations over a four-day period during April 2015 were analyzed to calibrate a numerical sediment transport model of Cook Inlet, AK. The field data campaign was designed to collect suspended load and bedload field measurements and was carried out in two phases. During Phase 1, both suspended load and bedload measurements were taken at approximately 55 ft water depth. The suspended sediment concentration was observed to be nearly uniform over the water column. Laboratory analysis showed the suspended sediment

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7

Bonilla-Porras, José A., Aronne Armanini, and Alessandra Crosato. "Extended Einstein's parameters to include vegetation in existing bedload predictors." Advances in Water Resources 152 (June 2021): 103928. http://dx.doi.org/10.1016/j.advwatres.2021.103928.

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8

Giberson, Donna J., and Daniel Caissie. "Stream habitat hydraulics: interannual variability in three reaches of Catamaran Brook, New Brunswick." Canadian Journal of Fisheries and Aquatic Sciences 55, no. 2 (1998): 485–94. http://dx.doi.org/10.1139/f97-247.

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The hydraulic habitat of 12 sites in a small salmon stream in central New Brunswick was investigated between 1992 and 1995 to determine patterns of habitat (substrate) stability between and within reaches. Stability was evaluated by measuring particle size distribution in replicated erosional and depositional sites in each reach and calculating the proportion of the bed predicted to be in motion at given flood flows. Erosional (riffle) sites in all reaches showed significant differences (ANOVA, p < 0.05) in substrate particle sizes from year to year, movement of embedded sediment samplers,

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9

Hosseini, Seyed Abbas, Abbas Abbaszadeh Shahri, and Reza Asheghi. "Prediction of bedload transport rate using a block combined network structure." Hydrological Sciences Journal 67, no. 1 (2022): 117–28. http://dx.doi.org/10.1080/02626667.2021.2003367.

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10

Khosravi, Khabat, James R. Cooper, Prasad Daggupati, Binh Thai Pham, and Dieu Tien Bui. "Bedload transport rate prediction: Application of novel hybrid data mining techniques." Journal of Hydrology 585 (June 2020): 124774. http://dx.doi.org/10.1016/j.jhydrol.2020.124774.

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