Contrasting Groundwater and Streamflow Ages at the Maimai Watershed
Bibliographic record
Abstract
Abstract Understanding the links between groundwater age, runoff generation processes, and their effects on stream water transit time (TT) is a major research challenge. Here we present new tritium age dating and hydrogeological characterization from 40 bedrock wells drilled at the intensively studied Maimai Experimental Watershed in New Zealand. We investigated the extent, dynamics, and age of the groundwater in a 4.5 ha headwater catchment over a 400 day period. In particular, we explored the controls of bedrock structure on aquifer dynamics, the aquifer flow domain and its influence on time‐varying stream water TT. We show that low permeability hillslope bedrock minimizes deep recharge, thereby regulating groundwater age, stream water MTT, and surface water‐groundwater interaction. Two distinct hydrologic units can represent catchment storage: shallow young soil storage and deep much older bedrock groundwater. Groundwater ages near discharge zones were up to 23 years compared to soil water ages that ranged between 0.1 and 0.5 years. This difference in age for the two main storages resulted in contrasting seasonal stream water TT response. During the 8 month wet season, stream water TT was young and stable while stream water TT in the slightly drier summer season was highly dynamic. These qualitative field observations are a process exemplar that support the Berghuijs and Kirchner (2017) quantitative descriptions of preferential release of young streamflow; and for the Maimai catchment, support the notion that most groundwater is exchanged only slowly with the surface and is therefore relatively old.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".