Pore water pressure assessment in a forest watershed: Simulations and distributed field measurements related to forest practices
Bibliographic record
Abstract
A distributed shallow groundwater model related to slope stability is described to assess the spatial distribution of pore water pressure in steep forested terrain in British Columbia. Additionally, effects of timber harvesting and roads on measured changes in pressure head during rainstorms were evaluated for the first time to assess the need for incorporating different hydrological components in the event‐driven distributed model. Although explicit spatial quantification of pore water pressure requires many measurements for accurate prediction, model performance using average parameter values was reasonable when compared with pressure heads measured at nine spatially distributed sites. Increases in maximum pressure head (varying from 9 to 28 cm) between preharvesting (after road construction) and postharvesting rainstorm events were observed in seven of nine sites. The remaining two sites showed either a small decrease (≈5 cm) or similar peak pressure heads following harvesting. Peak pressure head evaluated at one piezometer located 46 m downslope of the road decreased substantially (≈50 cm) after road construction during moderate rainstorms and then recovered following harvesting. Piezometric responses in sites upslope of the road were not affected by road construction but did increase after harvesting. Moderate storms caused the largest relative increases in pressure head between preharvesting (after roads) and postharvesting conditions; such increases were small during large storms, lending support to the idea that timber harvesting in temperate forests enhances hydrologic response only during small and moderate storms. Since landslides in coastal Pacific Northwest are typically caused by large winter rainstorms, it appears more justified to include better spatial representation of soil physical and engineering parameters in the distributed shallow groundwater model compared to specifying evapotranspiration; road hydrology may, however, need to be included.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| 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 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".