Sediment budget in the Ucayali River basin, an Andean tributary of the Amazon River

Santini, William; Martinez, Jean‐Michel; Espinoza-Villar, Raúl; Cochonneau, Gérard; Vauchel, Philippe; Moquet, Jean-Sébastien; Baby, Patrice; Espinoza, Jhan-Carlo; Lavado, Waldo; Carranza, Jorge; Guyot, Jean‐Loup

doi:10.5194/piahs-367-320-2015

Cited by 16 publications

(24 citation statements)

References 22 publications

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“…The southern (upstream) hot spot lied directly to the eastern face of the steep Shiras, while the northern hot spot was immediately downstream of the Pachitea River tributary which drains the western slopes of the Shiras. The Pachitea River alone accounts for 17% of the Ucayali's suspended sediment load immediately downstream its confluence [ Santini et al ., ]. The dead zone of migration (km 160–175) between the hot spots corresponded to the tapering off of the Shira Range.…”

Section: Results: the Morphodynamic Evolution Of The Ucayali Rivermentioning

confidence: 99%

“…The remarkable multiscale spatiotemporal variability of planform evolution along the Ucayali River implies multiple controls on change. Two migration hot spots and a dead‐zone fed (or starved) by sediment loads along the Ucayali demonstrate a nonuniform spatial control on migration rates imposed by local sediment inputs from the Shira Range [see also Santini et al ., ]. The identification of localized sediment‐driven migration complements the work of Constantine et al .…”

Section: Discussionmentioning

confidence: 99%

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High spatiotemporal resolution of river planform dynamics from Landsat: The RivMAP toolbox and results from the Ucayali River

Schwenk

Khandelwal

Fratkin

et al. 2017

Earth and Space Science

133

121

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Quantifying planform changes of large and actively migrating rivers such as those in the tropical Amazon at multidecadal time scales, over large spatial domains, and with high spatiotemporal frequency is essential for advancing river morphodynamic theory, identifying controls on migration, and understanding the roles of climate and human influences on planform adjustments. This paper addresses the challenges of quantifying river planform changes from annual channel masks derived from Landsat imagery and introduces a set of efficient methods to map and measure changes in channel widths, the locations and rates of migration, accretion and erosion, and the space-time characteristics of cutoff dynamics. The techniques are assembled in a comprehensive MATLAB toolbox called RivMAP (River Morphodynamics from Analysis of Planforms), which is applied to over 1500 km of the actively migrating and predominately meandering Ucayali River in Peru from 1985 to 2015. We find multiscale spatial and temporal variability around multidecadal trends in migration rates, erosion and accretion, and channel widths revealing a river dynamically adjusting to sediment and water fluxes. Confounding factors controlling planform morphodynamics including local inputs of sediment, cutoffs, and climate are parsed through the high temporal analysis.

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Section: Results: the Morphodynamic Evolution Of The Ucayali Rivermentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

High spatiotemporal resolution of river planform dynamics from Landsat: The RivMAP toolbox and results from the Ucayali River

Schwenk

Khandelwal

Fratkin

et al. 2017

Earth and Space Science

133

121

View full text Add to dashboard Cite

show abstract

“…Thus, the numerous water supplies from the Ecuadorian subbasins smooth the seasonality of the Marañon River flow regime. Located further to the south, the Ucayali Basin experiences a pronounced dry season (Ronchail and Gallaire, 2006;Garreaud et al, 2009;Lavado et al, 2011;Santini et al, 2014).…”

Section: Hydrological Data Acquisitionmentioning

confidence: 99%

An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland

et al. 2019

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Abstract. Because increasing climatic variability and anthropic pressures have affected the sediment dynamics of large tropical rivers, long-term sediment concentration series have become crucial for understanding the related socioeconomic and environmental impacts. For operational and cost rationalization purposes, index concentrations are often sampled in the flow and used as a surrogate of the cross-sectional average concentration. However, in large rivers where suspended sands are responsible for vertical concentration gradients, this index method can induce large uncertainties in the matter fluxes. Assuming that physical laws describing the suspension of grains in turbulent flow are valid for large rivers, a simple formulation is derived to model the ratio (α) between the depth-averaged and index concentrations. The model is validated using an exceptional dataset (1330 water samples, 249 concentration profiles, 88 particle size distributions and 494 discharge measurements) that was collected between 2010 and 2017 in the Amazonian foreland. The α prediction requires the estimation of the Rouse number (P), which summarizes the balance between the suspended particle settling and the turbulent lift, weighted by the ratio of sediment to eddy diffusivity (β). Two particle size groups, fine sediments and sand, were considered to evaluate P. Discrepancies were observed between the evaluated and measured P, which were attributed to biases related to the settling and shear velocities estimations, but also to diffusivity ratios β≠1. An empirical expression taking these biases into account was then formulated to predict accurate estimates of β, then P (ΔP=±0.03) and finally α. The proposed model is a powerful tool for optimizing the concentration sampling. It allows for detailed uncertainty analysis on the average concentration derived from an index method. Finally, this model could likely be coupled with remote sensing and hydrological modeling to serve as a step toward the development of an integrated approach for assessing sediment fluxes in poorly monitored basins.

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“…Thus, the numerous water supplies from the Ecuadorian sub-basins smooth the seasonality of the Marañon River flow regime. Located further to the south, the Ucayali basin experiences a pronounced dry season (Ronchail and Gallaire, 2006;Garreaud et al, 2009;Lavado et al, 2011;Santini et al, 2014).…”

Section: Hydrological Data Acquisitionmentioning

confidence: 99%

“…The samples are taken in the mainstream and at a fixed position. Additionally, HYBAM routinely uses moderate-resolution MODIS images to determine surface concentrations, and these values are calibrated with in situ radiometric measurements Santini et al, 2014;.…”

Section: Sampling Strategymentioning

confidence: 99%

An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland

Santini¹,

Camenen²,

Coz³

et al. 2019

Preprint

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Because increasing climatic variability and anthropic pressures have affected the sediment dynamics of large tropical rivers, long-term sediment concentration series have become crucial for understanding the related socio-economic and environmental impacts. For operational and cost rationalization purposes, index concentrations are often sampled in the flow and used as a surrogate of the cross-sectional average concentration. However, in large rivers where suspended sands are responsible for vertical concentration gradients, this index method can induce large uncertainties in the matter fluxes. 20Assuming that physical laws describing the suspension of grains in turbulent flow are valid for large rivers, a simple formulation is derived to model the ratio ( ) between index and average concentrations. The model is validated using an exceptional dataset (1330 water samples, 249 concentration profiles, 88 particle size distributions (PSDs) and 494 discharge measurements) that was collected between 2010 and 2017 in the Amazonian foreland. The prediction requires the estimation of the Rouse number ( ), which summarizes the balance between the suspended particle settling and the turbulent lift, weighted 25 by the ratio of sediment to eddy diffusivity ( ). Two particle size groups, washload and sand, were considered to evaluate .Discrepancies were observed between the evaluated and measured , that were attributed to biases related to the settling and shear velocities estimations, but also to diffusivity ratios ≠ 1. An empirical expression taking into account these biases was then formulated to predict accurate estimates of , then (∆ = ±0.03) and finally .The proposed model is a powerful tool for optimizing the concentration sampling. It allows for detailed uncertainty analysis 30 on the average concentration derived from an index method. Finally, this model can be coupled with remote sensing and hydrological modeling to serve as a step toward the development of an integrated approach for assessing sediment fluxes in poorly monitored basins.Earth Surf. Dynam. Discuss., https://doi.

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Sediment budget in the Ucayali River basin, an Andean tributary of the Amazon River

Cited by 16 publications

References 22 publications

High spatiotemporal resolution of river planform dynamics from Landsat: The RivMAP toolbox and results from the Ucayali River

High spatiotemporal resolution of river planform dynamics from Landsat: The RivMAP toolbox and results from the Ucayali River

An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland

An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland

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