Simulation of soil water content on a small reclaimed watershed in northern Alberta using the Root Zone Water Quality Model (RZQWM)
Bibliographic record
Abstract
A study was conducted at Syncrude Canada Ltd., Alberta, to evaluate the simulation of soil volumetric water content from the reclaimed slopes of the Southwest Sand Storage Facility using the Root Zone Water Quality Model (RZWQM). Soil water content measurements were conducted every 2 wk using a neutron moisture meter in 2001 (dry year) and 2002 (wet year). Two types of calibration and evaluation were performed: first, calibration using 2001 weather data (dry year) and evaluation using 2002 weather data (wet year) (herein referred to as method 1); second, calibration using 2002 weather data (wet year) and evaluation using 2001 weather data (dry year) herein referred to as (method 2). Results from the method 1 calibration for each tube indicated modeling efficiencies (EF) between −0.27 and 0.90, coefficients of determination (r2) between 0.13 and 0.97, and deviation (D, as %) of simulated from measured values of less than 5%. The model evaluation by tube location following method 1 calibration indicated EF values between −3.80 and 0.56, whereas r2 values ranged between 0.08 and 0.82. Although five out of eight tubes had D values > 5%, all except for one tube had D values < 20%. Method 2 calibration results for each tube indicated EF values of −0.34 to 0.85, r2 values of 0.07 to 0.85 and all D values < 5%. Results of the method 2 model evaluation by tube location indicated EF values of −10.15 to 0.75 (overall EF = −0.84), r2 values of 0.04 to 0.96 (overall r2 = 0.39) and D values of 2.6 to 48.6% (overall D = 19.8). Method 2 model evaluation results indicated EF values of −1.69, −3.85 and −0.01, for depths of 15, 25 and 35 cm, respectively. The D values were 27, 20 and 13%, respectively. Graphical displays indicated that during the evaluation process, the model generally tended to slightly under-estimate the wetter moisture conditions, regardless of whether data for a wet year or a dry year were used during the calibration process. Key words: Modeling, calibration method, soil water, land reclamation
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".