Inter-comparison of hydro-climatic regimes across northern catchments: synchronicity, resistance and resilience
Bibliographic record
Abstract
The higher mid-latitudes of the Northern Hemisphere are particularly sensitive to climate change as small differences in temperature determine frozen ground status, precipitation phase, and the magnitude and timing of snow accumulation and melt. An international inter-catchment comparison program, North-Watch, seeks to improve our understanding of the sensitivity of northern catchments to climate change by examining their hydrological and biogeochemical responses. The catchments are located in Sweden (Krycklan), Scotland (Mharcaidh, Girnock and Strontian), the United States (Sleepers River, Hubbard Brook and HJ Andrews) and Canada (Catamaran, Dorset and Wolf Creek). This briefing presents the initial stage of the North-Watch program, which focuses on how these catchments collect, store and release water and identify ‘types’ of hydro-climatic catchment response. At most sites, a 10-year data of daily precipitation, discharge and temperature were compiled and evaporation and storage were calculated. Inter-annual and seasonal patterns of hydrological processes were assessed via normalized fluxes and standard flow metrics. At the annual-scale, relations between temperature, precipitation and discharge were compared, highlighting the role of seasonality, wetness and snow/frozen ground. The seasonal pattern and synchronicity of fluxes at the monthly scale provided insight into system memory and the role of storage. We identified types of catchments that rapidly translate precipitation into runoff and others that more readily store water for delayed release. Synchronicity and variance of rainfall–runoff patterns were characterized by the coefficient of variation (cv) of monthly fluxes and correlation coefficients. Principal component analysis (PCA) revealed clustering among like catchments in terms of functioning, largely controlled by two components that (i) reflect temperature and precipitation gradients and the correlation of monthly precipitation and discharge and (ii) the seasonality of precipitation and storage. By advancing the ecological concepts of resistance and resilience for catchment functioning, results provided a conceptual framework for understanding susceptibility to hydrological change across northern catchments
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".