The persistence of snow on the ground affects the shape of streamflow hydrographs over space and time: a continental-scale analysis
Bibliographic record
Abstract
Snow persistence (SP) is a widely available remotely-sensed measure of snowpack accumulation and ablation, reflecting the duration of snow presence on the ground in a given year. Available local-scale studies showed that SP is associated with the average magnitude of streamflow. However, despite the intuitive relationship between SP and catchment storage/release functioning, the spatial and temporal links between the persistence of snow on the ground and the shape and functionality of streamflow hydrographs were not studied empirically and were not generalized to diverse climatic settings. This study empirically explores the spatial and temporal links that SP has with measures of hydrograph shape and variability during low-flow and high-flow conditions across continent-wide gradients of aridity and seasonality. In arid in-phase and wet out-of-phase climates, higher SP is spatially associated with a damper (i.e., less flashy) streamflow hydrograph during low-flow and high-flow conditions. This is shown by a larger ratio of baseflow to average flow, a larger ratio of extreme low-flow to average flow, lower low-flow variability, and lower high-flow variability. While SP is spatially associated with a damped hydrograph in both arid/in-phase and wet/out-of-phase climates, this effect is stronger in the former region. For example, the size of the nonlinear impact of SP on reducing low-flow and high-flow variabilities is larger in arid in-phase climates (−7.64, −3.44, respectively) than in wet out-of-phase climates (−4.34, −2.02, respectively). Temporal analyses for “typical snow-rich” catchments show that years with relatively higher SP may lead to relatively flashier streamflow hydrographs, with lower baseflow indices, lower ratios of extreme low-flow to average flow, higher ratios of extreme high-flow to average flow and higher high-flow variability. Such results 1) demonstrate the utility of SP as a globally available descriptor of streamflow hydrograph shape and variability in a wide diversity of climatic conditions, 2) highlight that climate-driven snow loss may lead to substantial changes to hydrograph form and functionality, and 3) indicate that space-time symmetry may not be a valid assumption in hydrology.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| 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".