Regional Groundwater Flow Modeling of the Chalk Aquifer of Beauvais, Paris Basin, North of France
Bibliographic record
Abstract
In this paper, a regional model to assess groundwater resources of the shallow groundwater system of Beauvais in the North of France has been satisfactorily completed using geophysical surveys and numerical modeling using MODFLOW-2000. A three-dimensional flow model has been developed for this aquifer using a large amount of available geological and hydrological data. The numerical flow model was calibrated and validated with datasets during 1998–2010. The calibration was done both by the automated parameter PEST and by the trial and error process. The main objective is to quantify the components of the groundwater mass balance, to estimate the hydraulic conductivity distribution and to characterize the hydrologic system. Furthermore, MODFLOW model was used to estimate the recharge, discharge, base flow and water Table fluctuation. Numerical simulations indicate that the Canada lake, located in the Therain valley, acts as a most discharge area for regional groundwater flow. Groundwater inflow from the recharge from Beauvais plateau which is mainly due to precipitation supplies the aquifer with most of its water. Following the calibration process, a sensitivity analysis was carried out. The results show that the aquifer exhibits the highest sensibility to the recharge parameters changes and hydraulic conductivity. The impact of the changes for both these hydraulic parameters appears to differ from large decrease to large increase in total groundwater discharge. The delicate shifts in the groundwater systems, which cause the changes in the recharge and discharge, clearly show the need for hydrological modeling.
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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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".