Glacial Effects on Discharge and Sediment Load in the Subarctic Tanana River Basin, Alaska
Bibliographic record
Abstract
About 5.6% of the drainage area of the Tanana River, Alaska, is covered by mountainous glacierized regions, and most of the other area by forests (51%) and wetlands (9%) with discontinuous permafrost. The water discharge and sediment load from glacierized and non-glacierized regions within the drainage area were represented by observed data of the proglacial Phelan Creek and the non-glacial Chena River, respectively, which are both the tributaries of the Tanana River and ultimately drain to the Yukon river basin. In the glacier-melt periods of 2007 and 2008, the runoff rate and suspended sediment concentration in Phelan Creek was 15 times and 36 times as high as those in the non-glacial Chena River, respectively. As a result, the mean sediment yield in the glacier-melt periods of 2007 and 2008 for Phelan Creek (24.8 t km−2 day−1) was estimated to be 640 times as high as that in the Chena River (0.039 t km−2 day−1). Hence, the glacierized regions were considered to be a major source of the fluvial sediment. In order to quantify the contribution of water discharge and sediment load from the glacierized regions to those of the Tanana River, the time series of water discharge, Q, and sediment load, L, in the glacier-melt periods were simulated by a tank model coupled with the L-Q equations (Nash-Sutcliffe efficiency coefficients, 0.41 to 0.82). The model indicates that the glacier-melt discharge accounted for 26–57% of the Tanana discharge, while the sediment load from the glacierized regions solely accounted for 76–94% of the Tanana sediment load. The remaining contribution (6–24%) of the sediment load was probably due to the fluvial resuspension of glacial sediment deposited previously in the river channels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".