Applications of Hydrochemical Models for Groundwater in Korea
Bibliographic record
Abstract
The variation patterns of groundwater mobility and chemical distribution are regarded as a very important factor for determining the geochemical features and therefore, the classifications of groundwater based on the chemical properties are highly valued for the expansion of study areas for setting up the regulations and management plans of governmental level for the preservation of local groundwater. Based on these prerequisites, in this study we focused on the evaluations, the comparison of the physiochemical characteristics and distribution of cations and anions in groundwater samples sampled in rural areas of Korea. The major goals of this study were classified as four categories such as followings; 1. On-site monitoring of groundwater qualities by instrumental and laboratory experiment, 2. Classifications of groundwater by using of Piper, Gibbs and Chadah diagram methods, 3. Tracking of the origins of anions and cations by using of rock-dominance types and relative ionic distributions. As a result of this study, the classifications of groundwater based on the Piper diagram showed that the groundwater type is grouped as the Ca2+-(Cl--NO3-) and Ca2+-HCO3- type groups and these types are known as the general features of groundwater in Korea. And the tracking of dominance types (classified as evaporation, rock, precipitation) based on the Gibbs diagram have shown that the origins of anions and cations in groundwater are the rock-dominance. In the applications of CAI 1 and CA 2, the negative values were more dominance than positive values so there might be reverse ion reaction between groundwater and rock-soils. Finally, by the carbonate weathering, silicate weathering and evaporation diagrams there were more complex mechanisms in chemical evolutions induced by the lithological influences such as weathering processes, ion exchange and other anthropogenic sources.
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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".