Topic
Stream power
About: Stream power is a research topic. Over the lifetime, 1135 publications have been published within this topic receiving 51324 citations.
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TL;DR: Findings show that V* is best explained using only watershed scale variables, including negative correlations with relief ratio and basin precipitation index, and positive correlations with maximum slope and circularity.
Abstract: Lithology is one of many factors influencing the amount, grain size distribution, and location of fine sediment deposition on the bed of mountain stream channels. In the Oregon Coast Range, 18 pool-riffle stream reaches with similar slope and intact riparian area and relatively unaffected by logjams were surveyed for assessment of fine sediment deposition. Half of the streams were in watersheds underlain by relatively erodible sandstone. The other half were underlain by a more resistant basalt. Channel morphology, hydraulic variables, particle size, relative pool volume of fine sediment (V*), and wood characteristics were measured in the streams. A significantly higher amount of fine sediment was deposited in the sandstone channels than in the basalt channels, as indicated by V*. Grab samples of sediment from pools also were significantly finer grained in the sandstone channels. Geographic information systems (GIS) software was used to derive several variables that might correlate with fine sediment deposition. These variables were combined with those derived from field data to create multiple linear regression models to be used for further exploration of the type and relative influence of factors affecting fine sediment deposition. Lithology appeared to be significant in some of these models, but usually was not the primary driver. The results from these models indicate that V* at the reach scale is best explained by stream power per unit area and by the volume of wood perpendicular to the flow per channel area (R2 = 0.46). Findings show that V* is best explained using only watershed scale variables, including negative correlations with relief ratio and basin precipitation index, and positive correlations with maximum slope and circularity.
24 citations
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TL;DR: In this article, a comparative geomorphic analysis of three watersheds underlain by sandstones and shales of the Acadian clastic wedge is presented, where the authors examine sediment-storage volumes in valley bottoms in tandem with morphometric analyses and the distribution of bedrock channels to make inferences regarding controls on sedimenttransport efficiency in the central Appalachians.
23 citations
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TL;DR: An extremal hypothesis is presented, namely, an alluvial channel attains a stable width when the rate of change of unit stream power with respect to its width is a minimum.
Abstract: Alluvial channels, in the context of this paper, are unlined man-made channels with predetermined bed slopes used to convey water that carries sediment. An extremal hypothesis is presented, namely, an alluvial channel attains a stable width when the rate of change of unit stream power with respect to its width is a minimum. An easy-to-use width control parameter is presented and compared with a form of Lacey's silt factor. The hypothesis is tested on data from canals located in the Punjab and Sind provinces of Pakistan.
23 citations
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19 May 2017TL;DR: In this article, the authors explore the sensitivity of the classic end-member landscape evolution models and the sediment fluxes they produce to a change in precipitation rates and find that both models have a response time that has a proportionality to the precipitation rate that follows a negative power law.
Abstract: Laboratory-scale experiments of erosion have
demonstrated that landscapes have a natural (or intrinsic) response time to a
change in precipitation rate In the last few decades there has been growth
in the development of numerical models that attempt to capture landscape
evolution over long timescales However, there is still an uncertainty
regarding the
validity of the basic assumptions of mass transport that are made in deriving
these models In this contribution we therefore return to a principal
assumption of sediment transport within the mass balance for surface
processes; we explore the sensitivity of the classic end-member landscape
evolution models and the sediment fluxes they produce to a change in
precipitation rates One end-member model takes the mathematical form of a
kinetic wave equation and is known as the stream power model, in which sediment
is assumed to be transported immediately out of the model domain The second
end-member model is the transport model and it takes the form of a diffusion
equation, assuming that the sediment flux is a function of the water flux and
slope We find that both of these end-member models have a response time that
has a proportionality to the precipitation rate that follows a negative power
law However, for the stream power model the exponent on the water flux term
must be less than one, and for the transport model the exponent must be
greater than one, in order to match the observed concavity of natural
systems This difference in exponent means that the transport model generally
responds more rapidly to an increase in precipitation rates, on the order of
105 years for post-perturbation sediment fluxes to return to within
50 % of their initial values, for theoretical landscapes with a scale of
100×100 km Additionally from the same starting conditions, the
amplitude of the sediment flux perturbation in the transport model is
greater, with much larger sensitivity to catchment size An important finding
is that both models respond more quickly to a wetting event than a drying
event, and we argue that this asymmetry in response time has significant
implications for depositional stratigraphies Finally, we evaluate the extent
to which these constraints on response times and sediment fluxes from simple
models help us understand the geological record of landscape response to
rapid environmental changes in the past, such as the Paleocene–Eocene thermal
maximum (PETM) In the Spanish Pyrenees, for instance, a relatively rapid (10
to 50 kyr) duration of the deposition of gravel is observed for a climatic shift
that is thought to be towards increased precipitation rates We suggest that the
rapid response observed is more easily explained through a diffusive
transport model because (1) the model has a faster response time, which is consistent
with the documented stratigraphic data, (2) there is a high-amplitude spike
in sediment flux, and (3) the assumption of instantaneous transport is
difficult to justify for the transport of large grain sizes as an alluvial
bedload Consequently, while these end-member models do not reproduce all
the complexity of processes seen in real landscapes, we argue that variations
in long-term erosional dynamics within source catchments can fundamentally
control when, how, and where sedimentary archives can record past
environmental change
23 citations
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TL;DR: In this article, the authors analyzed grain size distribution patterns in a point bar system of the Usri River, India, in the light of log-normal, log-hyperbolic and log-skew-Laplace distribution models.
Abstract: Grain-size distribution patterns in a point bar system of the Usri River, India, were critically analysed in the light of log-normal, log-hyperbolic and log-skew-Laplace distribution models Sand samples were collected from the cross-bedding foreset of different sizes of bedform; the objectives were to (i) study whether bedform heights have any role in grain-size distribution patterns, (ii) offer a best-fit statistical model, (iii) study the downstream variation of size-sorting in a point bar system, and (iv) study the mechanism of grain sorting
The results indicate that the bedform heights have no role in grain-size distribution patterns Quantitatively when the errors in three distribution models were analysed, it was observed that the log-normal distribution is the best-fit statistical model and the next one is the log-skew-Laplace However, in the upper reaches of the river, log-normal distribution is the best-fit model in the case of large bedforms, whereas in the lower reaches the log-normal model is the best-fit one in the case of small bed forms
It is also observed that within a point bar, for large and small bedforms, there is a tendency for mean grain size to decrease downstream Between point bars for large bedforms there is no consistency in decreasing grain size downstream, whereas for small bed forms the decrease of grain size downstream is observed except near the confluence at Palkia
With distance of transport, the coarser and finer fractions of sediments are gradually chopped off The coarser fractions are buried below the advancing bedforms on the lee sides and the finer ones are transported further downstream Thus the finer admixture giving rise to the fining-upward sequence overlies a carpet of coarser materials This mechanism provides a clue to the process of grain sorting in the fluvial environment
An interpretation has been offered for the log-normality of the grain-size distribution pattern During prolonged transportation in a fluvial environment, the larger grain-size fractions are gradually chopped off and buried below the advancing bedforms on their lee sides On the other hand, the finer fractions are transported further downstream in suspension Thus the narrow, intermediate size fraction takes active part in the distribution patterns leading to the generation of unimodality and a symmetric distribution pattern downstream, which are the main criteria for log-normality Similarly, increase of bedform size is the effect of increase of stream power and Froude number leading to the selective segregation of bed materials Thus the intermediate size fractions take a more active part than the coarser and the finer size fractions in developing log-normality
Besides the hydrodynamic parameters of the Usri, coarsening of grain size downstream has been attributed to (i) the aggrading nature of the Usri downstream, and (ii) the contribution of coarser materials to the Usri by its tributaries and bank erosion Copyright © 2006 John Wiley & Sons, Ltd
23 citations