Regional groundwater flow in mountainous terrain: Three‐dimensional simulations of topographic and hydrogeologic controls
Bibliographic record
Abstract
This study uses numerical simulations to define the salient controls on regional groundwater flow in 3‐D mountainous terrain by systematically varying topographic and hydrogeologic variables. Topography for idealized multiple‐basin mountainous terrain is derived from geomatic data and literature values. Water table elevation, controlled by the ratio of recharge to hydraulic conductivity, largely controls the distribution of recharged water into local, regional, and perpendicular flow systems, perpendicular flow being perpendicular to the regional topographic gradient. Both the relative (%) and absolute (m3/d) values of regional flow and perpendicular flow are examined. The relationship between regional flow and water table elevation is highly nonlinear. With lower water table elevations, relative and absolute regional flow dramatically increase and decrease, respectively, as the water table is lowered further. However, for higher water table elevations above the top of the headwater stream, changes in water table elevation have little effect on regional flow. Local flow predominates in high water table configurations, with regional and perpendicular flow <15% and <10%, respectively, of total recharge in the models tested. Both the relative and the maximum absolute regional flow are directly controlled by the degree of incision of the mountain drainage network; the elevation of mountain ridges is considerably less important. The percentage of the headwater stream with perennial streamflow is a potentially powerful indicator of regional flow in all water table configurations and may be a good indicator of the susceptibility of mountain groundwater systems to increased aridity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".