Recharge Estimation for Transient Ground Water Modeling
Why this work is in the frame
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Bibliographic record
Abstract
Reliable ground water models require both an accurate physical representation of the system and appropriate boundary conditions. While physical attributes are generally considered static, boundary conditions, such as ground water recharge rates, can be highly variable in both space and time. A practical methodology incorporating the hydrologic model HELP3 in conjunction with a geographic information system was developed to generate a physically based and highly detailed recharge boundary condition for ground water modeling. The approach uses daily precipitation and temperature records in addition to land use/land cover and soils data. The importance of the method in transient ground water modeling is demonstrated by applying it to a MODFLOW modeling study in New Jersey. In addition to improved model calibration, the results from the study clearly indicate the importance of using a physically based and highly detailed recharge boundary condition in ground water quality modeling, where the detailed knowledge of the evolution of the ground water flowpaths is imperative. The simulated water table is within 0.5 m of the observed values using the method, while the water levels can differ by as much as 2 m using uniform recharge conditions. The results also show that the combination of temperature and precipitation plays an important role in the amount and timing of recharge in cooler climates. A sensitivity analysis further reveals that increasing the leaf area index, the evaporative zone depth, or the curve number in the model will result in decreased recharge rates over time, with the curve number having the greatest impact.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 it