The role of soil water repellency in overland flow generation in pine and eucalypt forest stands in coastal Portugal
Bibliographic record
Abstract
Soil water repellency is now known to occur in diverse soils in various parts of the world. One of the possible adverse effects of soil water repellency is that it can reduce infiltration capacity and hence, on sloping terrain, enhance overland flow and soil erosion. The main aim of the present work is to assess the effects of soil water repellency on surface runoff production in the inner coastal dune areas of central Portugal. This was done for a pine and a eucalypt forest stand and, within each stand, for 2 slopes with contrasting aspect and somewhat different slope angles. Overland flow was measured for 4 pairs of unbounded plots of about 5 m2 at fortnightly intervals from February to October 2001. Over the same period, soil water repellency at and immediately below the soil surface was measured next to the plots at monthly intervals. The runoff–repellency relationship was also studied by carrying out rainfall simulation experiments on 0.24-m2 plots and associated repellency measurements. The effect of soil water repellency was most clearly demonstrated by statistically significant higher runoff coefficients under strong-to-extremely than under none-to-slightly hydrophobic conditions immediately below the soil surface. Such a difference in runoff over the measurement period was, however, restricted to 2 unbounded plots, both of which were located on the eucalypt slope with a southerly aspect and the greater slope angle. At the scale of these plots, the increase in runoff coefficient due to soil water repellency is moderate, when integrated over the entire period of strong–extremely repellent conditions, but can be quite substantial for individual 2-weekly periods. With respect to the observed differences in runoff between plots, be it plots on the same slope or not, it has proved difficult to distinguish the effect of soil water repellency from that of other factors likely to affect overland flow generation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".