Understanding the Role of Groundwater in a Remote Transboundary Lake (Hulun Lake, China)
Bibliographic record
Abstract
Hulun Lake, located in a remote, semi-arid area in the northeast part of Inner Mongolia, China, shares a transboundary basin with Mongolia and supports a unique wetland ecosystem that includes many endangered species. Decadal scale decreases in the lake stage and increased salinity make an understanding of the lake’s water and salt sources critical for appropriate design of strategies to protect and manage the lake. Multiple tracers (chloride, and δ18O and δ2H in water) in samples collected from lake water, rivers, and nearby water wells were used in conjunction with an annual water balance based on historic data to better understand the lake’s major water and salt sources. The average annual water balance was conducted for two time periods: 1981–2000 and 2001–2013. The contribution of river discharge to the annual lake input decreased by half (from 64% to 31%) between the two time periods, while the volumetric contribution of groundwater discharge increased four-fold (from about 11% to about 50% of the total lake input). Significant evaporation was apparent in the stable isotope composition of the present-day lake water, however, evaporation alone could not account for the high lake water chloride concentrations. Limited domestic well water sampling, a regional salinity survey, and saline soils suggest that high chloride groundwater concentrations exist in the region south of the lake. The chloride mass balance suggested that groundwater currently contributes more than 90% of the annual chloride loading to the lake, which is likely four times greater than the earlier period (1981–2000) with lower groundwater input. The use of water and chloride mass balances combined with water isotope analyses could be applied to other watersheds where hydrologic information is scarce.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".