Assessing basin storage: Comparison of hydrometric‐ and tracer‐based indices of dynamic and total storage
Bibliographic record
Abstract
Abstract Storage is a fundamental but elusive component of drainage basin function, influencing synchronization between precipitation input and streamflow output and mediating basin sensitivity to climate and land use/land cover (LULC) change. We compare hydrometric and isotopic approaches to estimate indices of dynamic and total basin storage, respectively, and assess inter‐basin differences in these indices across the Oak Ridges Moraine (ORM) region of southern Ontario, Canada. Dynamic storage indices for the 20 study basins included the ratio of baseflow to total streamflow (baseflow index BFI), Q 99 flow and flow duration curve (FDC) slope. Ratios of the standard deviation of the streamflow stable isotope signal relative to that of precipitation were determined for each basin from a 1 year bi‐weekly sampling program and used as indicators of total storage. Smaller ratios imply longer water travel times, smaller young water fractions (F yw, < ~2–3 months in age) in streamflow and greater basin storage. Ratios were inversely related to BFI and Q 99, and positively related to FDC slope, suggesting longer travel times and smaller F yw for basins with stable baseflow‐dominated streamflow regimes. Inter‐basin differences in all indices reflected topographic, hydrogeologic and LULC controls on storage, which was greatest in steep, forest‐covered headwaters underlain by permeable deposits with thick and relatively uniform unsaturated zones. Nevertheless, differential sensitivity of indices to controls on storage indicates the value of using several indices to capture more completely how basin characteristics influence storage. Regression relationships between storage indices and basin characteristics provided reasonable predictions of aspects of the streamflow regime of test basins in the ORM region. Such relationships and the underlying knowledge of controls on basin storage in this landscape provide the foundation for initial predictions of relative differences in streamflow response to regional changes in climate and LULC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 source (direct Gemma or distilled Codex), 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".