Characteristics of Soil Water, Salt and Nitrogen Distribution, and Accumulation on Forest Land, Cropland, Playa and Grassland in Bashang Area of Hebei Province
Bibliographic record
Abstract
[Objective] The distribution of soil water, salt and nitrogen in arid and semi-arid areas were analyzed in order to provide a basis for preventing and controlling non-point source pollution of groundwater and sustainably utilizing water and soil resources. [Methods] Four typical land use types (forest land, cropland, playa and grassland) in the Bashang area of Hebei Province were selected as the study objects. By analyzing changes in water, salt and nitrate of soils, we determined the distribution patterns of water, salinity, and nitrogen in the soil profiles of the different land use types. [Results] ① The soil water and salt content in the playa of Anguli Lake was the highest among the different land use types, with an average water content of 60.18%. The distributions of soil water and salt showed medium variability, with a greater degree of variability in water content. ② The same distributions of soil water and salt in the 0—220 cm soil profile were observed for forest land, farmland, and the playa (all except grassland) of Anguli Lake, exhibiting an oscillating shape, homogeneous shape, and bottom aggregation shape, respectively. ③ Saltions for the four land use types were significantly different (p<0.05), and their compositions were dominated by SO42-, while K+, Mg2+ and Ca2+ were relatively scarce. ④ The average nitrate content in the soil profile of the playa of Anguli Lake was as high as 134.18 mg/kg. Its distributions in forest land and farmland exhibited accumulation in topsoil, characterized by less in the middle and more at the top and bottom of the playa of Anguli Lake. The accumulation of nitrate in the upper soil layer of grassland was obvious. ⑤ The nitrate of soils of forest land, cropland, playa and grassland showed highly significant positive correlations with K+, which was the main factor that controlled the variation of nitrate. [Conclusion] The distributions of soil water, salt and nitrogen on forest land, cropland, playa and grassland in the Bashang area of Hebei Province had obvious variability, and the soil water, salt, and nitrogen content in the playa of Anguli Lake was significantly higher than seen for the other three land use types, thereby posing a serious risk of leaching to groundwater.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".