Accuracy of Saturated Soil Hydraulic Conductivity Estimated from Numerically Simulated Single‐Ring Infiltrations
Bibliographic record
Abstract
Core Ideas The accuracy of the PI method in estimating soil K s was tested by numerical simulations. Estimated K s using two‐ponding‐depth and multiple‐ponding‐depth infiltration were compared. Transient and steady‐state infiltration data for six soils were used to estimate K s . The PI should yield more accurate K s estimates in coarse‐ than fine‐textured soils. The transient method does not solve the K s inaccuracy problems in fine‐textured soils. The single‐ring pressure infiltrometer (PI) method is widely used to determine saturated soil hydraulic conductivity, K s , directly in the field. The original and still most common way to analyze the data makes use of the steady‐state model developed by the Canadian School in the 90s and two (two‐ponding‐depth, TPD, approach) or more (multiple‐ponding‐depth, MPD, approach) depths of ponding. The so‐called Wu method based on a generalized infiltration equation allows analysis of the transient infiltration data collected by establishing a single ponding depth of water on the infiltration surface. This investigation, making use of simulated infiltration runs for initially unsaturated sand to silty clay loam soils, showed that, with a run duration of practical interest (e.g., 2 h), the PI can be expected to yield more accurate estimates of K s in coarse‐textured soils than in fine‐textured soils even if the transient method is used instead of the steady‐state method. Performing a three‐level experiment and analyzing the estimated steady‐state infiltration rates with both the TPD and MPD approaches is a way to predict the reliability of the estimated K s value. The K s accuracy should be acceptable if the two approaches yield similar results. Otherwise, the MPD approach should be expected to yield more accurate K s estimates than the TPD approach. The transient method does not solve the K s inaccuracy problems in fine‐textured soils because obtaining accurate K s data requires that the portion of total infiltration varying linearly with time represent a high percentage of total infiltration, but this percentage is small in fine‐textured soils when the run does not exceed a few hours. This investigation opens some new perspective on the use of infiltration data to make predictions on the expected reliability of the K s calculations with reference to both steady‐state and transient data analysis procedures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".