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Record W7056422919

An Evaluation of Sediment Transport in the Columbia River Basin: Before and After System-Wide Flow Regulation

2024· article· en· W7056422919 on OpenAlexaboutno aff

Bibliographic record

VenuePDXScholar (Portland State University) · 2024
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsHydrology (agriculture)SedimentSediment transportErosionDeposition (geology)STREAMSFlood mythSedimentary budgetStream power
DOInot available

Abstract

fetched live from OpenAlex

Erosion and sediment transport are ubiquitous in every riverine ecosystem. Aquatic habitat eroded and sediment removal for infrastructure require deposition of upstream material to maintain morphodynamic equilibrium. A large percentage of total sediment transport occurs during relatively brief high flow events throughout the water-year. Dams are known to modify the ability for streams to freely transport sediment. Depending on the river size and dam type, downstream movement of sediment can be inhibited or completely eliminated. On the Columbia River, 14 dams are situated between the tidal-zone to the headwaters in the Canadian Rocky Mountains. The main uses of the dams are navigation, flood control, and power generation. A majority of the dams are “run-of-the-river” style installations without long-term storage capacity, because of high river flow and reservoir geometry. Run-of-the-river dams generally allow some sediment transport to occur even of the coarser grain sizes. In 1970, the final dams were almost completed on the mainstem Columbia River and lower Snake River, this date also marks the beginning of complete system-wide flow regulation (SWFR). Sediment transport has been reduced by the implementation of SWFR, and not solely because dams are in place along the river. This study estimates sediment transport before and after 1970 to evaluate possible changes after complete SWFR began. Pre-SWFR data from 1962-63 and 1968-69 have been digitized for 4 sites along the mainstem Columbia River and near the confluence of two of its largest tributaries. Post-SWFR sites were selected as close as possible to pre-SWFR data collection areas and were obtained from the US Geological Survey (USGS) and the US Army Corps of Engineers (USACE). Pre- and post-SWFR models were created using water-discharge as an explanatory variable to hindcast and forecast total, fine, and coarse sediment transport for the period of 1887 to 2023 for Warrendale, Willamette and Beaver sites, 1933 to 2023 for the Pasco site, 1958 to 2023 for the Snake River site, and 1960 to 2023 for the Vancouver site. Reconstruction of the entire period of record at each site is used to validate each model. Additional model validation occurred on the Lower Columbia River and the Willamette River with recently installed acoustic-derived sediment gages. Post-SWFR models match well with acoustic sediment predictions, but these modern observing systems have not recorded data during extreme events. Generally, models perform best using coarse sediment loads and show large decreases in sediment transport post-SWFR. Pre-SWFR models have R2 values ranging from 0.60 to 0.99; the best model fits are associated with the coarse sediment transport data. Post-SWFR models have R2 values ranging from 0.48 to 0.98 with coarse sediment transport again having the best fits. Hindcast sediment discharge daily values were summed over each water year and were used to evaluated changes in sediment transport over the entire available water discharge period. Sediment transport at mainstem Columbia River sites has declined 49% to 65% for total sediment transport, 31% to 67% for fine sediment transport, and 72% to 88% for coarse sediment transport.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.190
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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