Groundwater Subsidy From Headwaters to Their Parent Water Watershed: A Combined Field‐Modeling Approach
Bibliographic record
Abstract
Abstract Headwater groundwater subsidy, defined here as out‐of‐catchment groundwater flow contribution from a headwater catchment to its larger parent watershed (i.e., higher‐order stream), can influence the water quality and quantity of regional water resources. But the integrated flow and transport modeling approaches currently being implemented to quantify this subsidy are limited by an absence of critical field observations, such as water table dynamics and groundwater age that are required to test such models. Here we couple tracer (and hydrometric) observations from the well‐studied 4.5‐ha M8 headwater catchment in the Maimai experimental watershed with a new semianalytical free‐surface integrated flow and transport model. Our main research goals are to quantify the magnitude, age, and flow paths of the headwaters groundwater subsidies at the Maimai experimental watershed. Additionally, we explore through virtual experiments the effects of watershed slope, watershed active thickness, and recharge rate on the age, flow path, and magnitude of out‐of‐catchment headwater groundwater subsidies versus within‐catchment (or local) groundwater flow contributions. Our results show that more than 50% of groundwater recharged in the Maimai headwaters subsidizes their parent watershed. The relative proportion of headwaters groundwater subsidies is inversely proportional to recharge rate and/or directly proportional to slope angle. Our results also show that the age of the headwater groundwater subsidies is more than 500 years, almost 9 times older than the age of within‐catchment groundwater flow contributions. These findings highlight the need to consider headwaters groundwater subsidies in groundwater management area considerations.
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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 | 0.002 | 0.000 |
| 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 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.010 |
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; both teacher heads agree on what is shown here.
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".