HydroBudget – Groundwater recharge model in R
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
HydroBudget (HB) is a spatially distributed groundwater recharge (GWR) model that computes a superficial water budget on grid cells with outputs aggregated into monthly time steps. It was developed as an accessible and computationally affordable model to simulate GWR over large areas (thousands of km2, regional-scale watersheds) and for long time periods (decades), in cold and humid climates. The model is coded in R and was developed at UQAM by the team of Pr Marie Larocque’s research Chair (Water and land conservation) as part of a project funded by the Quebec Ministry of the Environment (Ministère de l’Environnement et de la Lutte contre les changements climatiques - MELCC). Results of GWR simulation over southern Quebec (Canada) with HB are presented in Dubois et al. (2021). Le model script is provided with an application example for the Petite du Chene River in southern Quebec and a User-guide. As of July 2023, the further development of the HydroBudget model will be included in the rechaRge package. More information can be found here: https://www.epfl.ch/labs/lch/research/water-and-groundwater-management/recharge-an-r-package-for-integrated-groundwater-recharge-modelling-in-r/ Additionally, the development of the code can now be followed here: https://github.com/gwrecharge
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it