Tracking downstream variability in large grain-size distributions in the South-Central Andes

  • Mixed sand- and gravel-bed rivers record erosion, transport, and fining signals in their bedload size distributions. Thus, grain-size data are imperative for studying these processes. However, collecting hundreds to thousands of pebble measurements in steep and dynamic high-mountain river settings remains challenging. Using the recently published digital grain-sizing algorithm PebbleCounts, we were able to survey seven large (>= 1,000 m2) channel cross-sections and measure thousands to tens-of-thousands of grains per survey along a 100-km stretch of the trunk stream of the Toro Basin in Northwest Argentina. The study region traverses a steep topographic and environmental gradient on the eastern margin of the Central Andean Plateau. Careful counting and validation allows us to identify measurement errors and constrain percentile uncertainties using large sample sizes. In the coarse >= 2.5 cm fraction of bedload, only the uppermost size percentiles (>= 95th) vary significantly downstream, whereas the 50th and 84th percentiles show lessMixed sand- and gravel-bed rivers record erosion, transport, and fining signals in their bedload size distributions. Thus, grain-size data are imperative for studying these processes. However, collecting hundreds to thousands of pebble measurements in steep and dynamic high-mountain river settings remains challenging. Using the recently published digital grain-sizing algorithm PebbleCounts, we were able to survey seven large (>= 1,000 m2) channel cross-sections and measure thousands to tens-of-thousands of grains per survey along a 100-km stretch of the trunk stream of the Toro Basin in Northwest Argentina. The study region traverses a steep topographic and environmental gradient on the eastern margin of the Central Andean Plateau. Careful counting and validation allows us to identify measurement errors and constrain percentile uncertainties using large sample sizes. In the coarse >= 2.5 cm fraction of bedload, only the uppermost size percentiles (>= 95th) vary significantly downstream, whereas the 50th and 84th percentiles show less variability. We note a relation between increases in these upper percentiles and along-channel junctions with large, steep tributaries. This signal is strongly influenced by lithology and geologic structures, and mixed with local hillslope input. In steep catchments like the Toro Basin, we suggest nonlinear relationships between geomorphic metrics and grain size, whereby the steepest parts of the landscape exert primary control on the upper grain-size percentiles. Thus, average or median metrics that do not apply weights or thresholds to steeper topography may be less predictive of grain-size distributions in such settings.show moreshow less

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Metadaten
Author details:Benjamin PurintonORCiDGND, Bodo BookhagenORCiDGND
DOI:https://doi.org/10.1029/2021JF006260
ISSN:2169-9003
ISSN:2169-9011
Title of parent work (English):Journal of geophysical research : F, Earth surface
Publisher:American Geophysical Union
Place of publishing:Washington
Publication type:Article
Language:English
Date of first publication:2021/08/05
Publication year:2021
Release date:2022/09/21
Tag:digital grain sizing; downstream fining; fluvial geomorphology; grain-size distribution; pebblecounts
Volume:126
Issue:8
Article number:e2021JF006260
Number of pages:29
First page:1
Last Page:29
Funding institution:DLRHelmholtz AssociationGerman Aerospace Centre (DLR) [DEM_CALVAL1028]; DFGGerman Research Foundation (DFG)European Commission [BO 2933/3-1]; BMBF LIDARFederal Ministry of Education & Research (BMBF); NEXUS funded through the MWFK Brandenburg, Germany; Projekt DEAL
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC classification:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer review:Referiert
Publishing method:Open Access / Hybrid Open-Access
License (German):License LogoCC-BY - Namensnennung 4.0 International
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