Transient, spatially varied groundwater recharge modeling
Bibliographic record
Abstract
The objective of this work is to integrate field data and modeling tools in producing temporally and spatially varying groundwater recharge in a pilot watershed in North Okanagan, Canada. The recharge modeling is undertaken by using the Richards equation based finite element code (HYDRUS‐1D), ArcGIS™, ROSETTA, in situ observations of soil temperature and soil moisture, and a long‐term gridded climate data. The public version of HYDUS‐1D and another version with detailed freezing and thawing module are first used to simulate soil temperature, snow pack, and soil moisture over a one year experimental period. Statistical analysis of the results show both versions of HYDRUS‐1D reproduce observed variables to the same degree. After evaluating model performance using field data and ROSETTA derived soil hydraulic parameters, the HYDRUS‐1D code is coupled with ArcGIS™ to produce spatially and temporally varying recharge maps throughout the Deep Creek watershed. Temporal and spatial analysis of 25 years daily recharge results at various representative points across the study watershed reveal significant temporal and spatial variations; average recharge estimated at 77.8 ± 50.8 mm/year. Previous studies in the Okanagan Basin used Hydrologic Evaluation of Landfill Performance without any attempt of model performance evaluation, notwithstanding its inherent limitations. Thus, climate change impact results from this previous study and similar others, such as Jyrkama and Sykes (2007), need to be interpreted with caution.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.014 |
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; both teacher heads agree on what is shown here.
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".