Exploring Groundwater Responses to the 2021 Drought and Atmospheric River Events across British Columbia, Canada
Bibliographic record
Abstract
Most studies on the impacts of extreme hydrometeorological events on hydrological processes have focused primarily on surface water systems rather than groundwater systems. This study explores and seeks to untangle the complex nature of groundwater dynamics and resilience across British Columbia (BC) in response to the 2021 heatwave-intensified drought and atmospheric rivers (ARs). Historically, there have been many episodic drought events along with substantially wet periods. However, 2021 marked an unprecedented year for the immediate co-occurrence of intense and extreme drought and deluge. This weather whiplash resulted in the lowest and highest groundwater levels on record for many wells across BC. The record meteorological drought, intensified by a 13-day heatwave in late June, affected the entire province and lasted for over 50 days in the south coast region. This was followed in November by the most intense ARs to make landfall on record in southwestern BC. Groundwater hydrograph anomalies for 2021 were computed relative to their short-term historical mean for 194 provincial observation wells across the province. The 2021 anomalies showed a limited but distinct range of responses to both the drought and ARs, and cluster into three response groups, largely associated with their respective hydroclimatic regime. Many coastal wells showed a strong response to drought; however, nearly all wells in the southern interior responded substantially, with groundwater levels significantly below their historical range by late summer. Presently, groundwater levels seem to have recovered across the province, especially on the coast. This resiliency is attributed in part to the ARs that made landfall since last year along with a particularly wet, La Niña winter. The majority of coastal wells showed a much stronger signal to the ARs compared to the interior or eastern BC wells, likely due to the more rapid and intense rainfall experienced in southwestern BC. Groundwater systems across BC were variably impacted by these hydrometeorological extremes, showcasing the need for focused and area-specific approaches to water allocation decisions in assuring sustainable withdrawal practices.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".