Reconstructing river flows remotely on Earth, Titan, and Mars
Bibliographic record
Abstract
Alluvial rivers are conveyor belts of fluid and sediment that provide a record of upstream climate and erosion on Earth, Titan, and Mars. However, many of Earth's rivers remain unsurveyed, Titan's rivers are not well resolved by current spacecraft data, and Mars' rivers are no longer active, hindering reconstructions of planetary surface conditions. To overcome these problems, we use dimensionless hydraulic geometry relations-scaling laws that relate river channel dimensions to flow and sediment transport rates-to calculate in-channel conditions using only remote sensing measurements of channel width and slope. On Earth, this offers a way to predict flow and sediment flux in rivers that lack field measurements and shows that the distinct dynamics of bedload-dominated, suspended load-dominated, and bedrock rivers give rise to distinct channel characteristics. On Mars, this approach not only predicts grain sizes at Gale Crater and Jezero Crater that overlap with those measured by the Curiosity and Perseverance rovers, it enables reconstructions of past flow conditions that are consistent with proposed long-lived hydrologic activity at both craters. On Titan, our predicted sediment fluxes to the coast of Ontario Lacus could build the lake's river delta in as little as ~1,000 y, and our scaling relationships suggest that Titan's rivers may be wider, slope more gently, and transport sediment at lower flows than rivers on Earth or Mars. Our approach provides a template for predicting channel properties remotely for alluvial rivers across Earth, along with interpreting spacecraft observations of rivers on Titan and Mars.
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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 | 0.000 | 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) | 0.000 | 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".