Flow dynamics in hyper-saline aquifers: hydro-geophysical monitoring and modeling
Bibliographic record
Abstract
Abstract. Saline–freshwater interaction in porous media is a phenomenon of practical interest particularly for the management of water resources in arid and semi-arid environments, where precious freshwater resources are threatened by seawater intrusion and where storage of freshwater in saline aquifers can be a viable option. Saline–freshwater interactions are controlled by physico-chemical processes that need to be accurately modeled. This in turn requires monitoring of these systems, a non-trivial task for which spatially extensive, high-resolution non-invasive techniques can provide key information. In this paper we present the field monitoring and numerical modeling components of an approach aimed at understanding complex saline–freshwater systems. The approach is applied to a freshwater injection experiment carried out in a hyper-saline aquifer near Cagliari (Sardinia, Italy). The experiment was monitored using time-lapse cross-hole electrical resistivity tomography (ERT). To investigate the flow dynamics, coupled numerical flow and transport modeling of the experiment was carried out using an advanced three-dimensional (3-D) density-driven flow-transport simulator. The simulation results were used to produce synthetic ERT inversion results to be compared against real field ERT results. This exercise demonstrates that the evolution of the freshwater bulb is strongly influenced by the system's (even mild) hydraulic heterogeneities. The example also highlights how the joint use of ERT imaging and gravity-dependent flow and transport modeling give fundamental information for this type of study.
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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 | 0.001 | 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 | 0.000 |
| 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".