Modeling groundwater responses to climate change in the Prairie Pothole Region
Bibliographic record
Abstract
Abstract. Shallow groundwater in the Prairie Pothole Region (PPR) is recharged predominantly by snowmelt in the spring and may supply water for evapotranspiration through the summer/fall. This two-way exchange is underrepresented in land-surface models. Furthermore, the impacts of climate change on the groundwater recharge are uncertain. In this paper, we use a coupled land and groundwater model to investigate the hydrologic cycle of shallow groundwater in the PPR and study its response to climate change at the end of the 21st century. The results show that the model reasonably simulates the water table depth (WTD) and the timing of recharge processes, but underestimates the seasonal variation of WTD, due to mismatches of the soil types between observations and the model. The most significant change under future climate occurs in the winter, when the warmer temperature changes the rain/snow partitioning, delay the time for snow accumulation/soil freezing while bringing forward early melting/thawing. Such changes lead to an earlier start to a longer recharge season, but with lower recharge rates. Different signals are shown in the eastern and western PPR in the future summer, with reduced precipitation and drier soils in the east but little change in the west. The annual recharge increased by 25% and 50% in the eastern and western PPR, respectively. Additionally, we found the mean and seasonal variation of the simulated WTD are sensitive to soil properties and fine-scale soil information is needed to improve groundwater simulation on a regional scale.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".