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Forecasts of water level during river floods require accurate predictions of the evolution of river dune dimensions, because the hydraulic roughness of the main channel is largely determined by the bed morphology. River dune dimensions are controlled by processes like merging and splitting of dunes. Particularly the process of dune splitting is still poorly understood and – as a result – not yet included in operational dune evolution models. In the current paper, the process of dune splitting is investigated by carrying out laboratory experiments and by means of a sensitivity analysis using a numerical dune evolution model. In the numerical model, we introduced superimposed TRIAS ripples (i.e. triangular asymmetric stoss side‐ripples) on the stoss sides of underlying dunes as soon as these stoss sides exceed a certain critical length. Simulations with the model including dune splitting showed that predictions of equilibrium dune characteristics were significantly improved compared to the model without dune splitting. As dune splitting is implemented in a parameterized way, the computational cost remains low which means that dune evolution can be calculated on the timescale of a flood wave. Subsequently, we used this model to study the mechanism of dune splitting. Literature showed that the initiation of a strong flow separation zone behind a superimposed bedform is one of the main mechanisms behind dune splitting. The flume experiments indicated that besides its height also the lee side slope of the superimposed bedform is an important factor to determine the strength of the flow separation zone and therefore is an important aspect in dune splitting. The sensitivity analysis of the dune evolution model showed that a minimum stoss side length was required to develop a strong flow separation zone. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   
2.
Natural Hazards - The article was published Open Access under the Dutch Compact Agreement; however, due to an internal system error, previous HTML rendering of the article did not reflect this.  相似文献   
3.
Hydrodynamic river models are applied to design and evaluate measures for purposes such as safety against flooding. The modelling of river processes involves numerous uncertainties, resulting in uncertain model results. Knowledge of the type and magnitude of these uncertainties is crucial for a meaningful interpretation of the model results. Uncertainty in the hydraulic roughness due to bed forms is one of the main contributors to the uncertainty in the modelled water levels. The aim of this study was to quantify the uncertainty in the bed form roughness under design conditions and quantify the effect on the design water levels in the Dutch river Waal. Five roughness models that predict bed form roughness based on measured bed form and flow characteristics were extrapolated to design conditions. The results show that the 95% confidence interval of the predicted Nikuradse roughness values under design conditions ranges from 0.32 to 1.03 m. This uncertainty was propagated through the two‐dimensional hydrodynamic model, WAQUA, by means of a Monte Carlo simulation for an idealized schematization of the Dutch river Waal. The uncertain bed form roughness results in an uncertainty in the design water levels, with a 95% confidence interval of 0.53 m, which is significant for Dutch river management practice. The uncertainty in the bed form roughness was mainly caused by a lack of knowledge about the physical process of bed form evolution that causes roughness. An improved estimation of bed form roughness can significantly reduce the uncertainty in the design water levels. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   
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