A Paradigm Shift in Hydrology: Storage Thresholds Across Scales Influence Catchment Runoff Generation
Bibliographic record
Abstract
Abstract A paradigm shift is occurring in the science surrounding runoff generation processes. Results of recent field investigations in landscapes and during periods previously unobservable are shaping new ideas on how runoff is generated and transferred from the hillslope to the catchment outlet. The previous paradigm saw runoff generation and contributing area variability as a continuum. The new paradigm is based not on continual storage satisfaction and runoff generation but threshold‐mediated, connectivity‐controlled processes dictated by heterogeneity in the catchment. This review focuses on the body of literature summarizing research on storage, storage thresholds and runoff generation, particularly over the last several years during which this paradigm shift has occurred. Storage thresholds that control the release of water exist at scales as small as the soil matrix and as large as the catchment. Hysteresis in storage–runoff relationships at all scales manifest because of these thresholds. Because storage thresholds at a range of scales have now been recognized as important, connectivity has become an important concept crucial to understanding how water is transferred through a catchment. This new paradigm requires basins to be instrumented within the context of a water budget investigation, with measurements taken within key catchment units, in order to be successful. New model approaches that incorporate connectivity are required to address the findings of field hydrologists. These steps are crucial if our community wishes to adopt the holisitic view of the catchment necessary to answer the questions posed to us by the society.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".