Evaluating the Ubiquity of Thresholds in Rainfall‐Runoff Response Across Contrasting Environments
Bibliographic record
Abstract
Abstract Thresholds in precipitation‐runoff relationships have been observed in numerous studies using scatter plots comparing meteorological factors and hydrologic response metrics. Most thresholds reported in the literature have been identified from relationships between meteorological factors that quantify volumes or depths of water (e.g., total event rainfall) and metrics capturing hydrologic response magnitude (e.g., runoff ratio), with a strong emphasis on hillslopes and catchments in temperate humid environments. Knowledge gaps, however, remain regarding the ubiquity of hydrologic thresholds across different climatic environments and different meteorological factors that affect different response metrics. This study therefore aimed to evaluate relationships for a wide range of meteorological factors and response metrics derived from event‐scale rainfall‐runoff analysis for 21 sites spanning seven contrasting geographic areas. Specifically, meteorological factors quantifying rainfall depth, rainfall intensity, and hydrologic abstractions related to evapotranspiration were considered, along with response metrics that describe response timing and response magnitude, leading to 4,557 relationships being evaluated. While rainfall depth thresholds were observed for most sites, rainfall intensity thresholds were also observed. Additionally, threshold behavior was shown to be sensitive to antecedent conditions over specific durations of time preceding a rainfall‐runoff event. The large number of relationships evaluated in this study allowed for the development of a typology of threshold dynamics and the formulation of hypotheses about dominant hydrological processes. This typology may not only promote standardized threshold descriptions but also make intersite comparisons of nonlinear rainfall‐runoff behavior easier.
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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 | 0.009 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".