Soil water dynamics under vegetation based on a contrastive experiment between vegetated and non-vegetated sites
Bibliographic record
Abstract
Vegetation plays an active role in soil water dynamics and water balance in atmosphere-soil-vegetation-groundwater system. Therefore, we characterised soil water transportation at depths of 0-4.0 m, induced by root water uptake of groundwater-dependent Salix across a whole growth stage, as well as taking place in non-vegetated soil, in the semi-arid Ordos basin of China. The results show that: soil moisture content showed clear heterogeneity under the combined influence of evaporation, rainfall and root water uptake. Thus, the soil profile was divided into the climate impacted layer, the transitional layer, and groundwater supporting layer. Root water uptake increased the variability of soil water in the vadose zone and changed the classification structure. The impacts of different rainfall regimes on soil moisture and vegetation response at the individual plant scale were systematically analysed. The rainwater infiltration hysteresis as connected to rainfall intensity, soil depth and the roots-system preferential channel were confirmed, as was the canopy-shading effect. Further, an exponential-logarithmic normal composite root water uptake distribution was obtained, via an inverse method. Of the accumulated 356.3 precipitation in 2016, the annual soil water increase was 97.9 mm for bare site, increased by 10.2% in total, accounting for 25.5% of the precipitation of that year. Conversely, for vegetated site, annual soil water decrease registered at 254.40 mm, decreased by 28.3% in total. The contrastive experiment indicates that root water uptake processes change the soil water flow field and aggravate water scarcity, resulting in soil desiccation in the deep local soil layers and groundwater depletion. The dried soil layers blocked water interchange, which is extremely detrimental to ecohydrological processes. Our results provide a scientific basis within which the hydrodynamic processes of vegetation in semi-arid regions may better be understood and inspire research to find a balance between groundwater management and vegetation replanting.
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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 | 0.000 | 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 | 0.001 |
| 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".