Reactivity of southern Quebec aquifers to meteorological and hydrological conditions
Bibliographic record
Abstract
Groundwater represents an important source of drinking water for 25% of the population in the province of Quebec (Canada) and for 80% of its rural population. The deployment of the Quebec Groundwater Observation Network (Réseau de suivi des eaux souterraines du Québec – RSESQ) since the start of the millennia provides important data on the dynamics of piezometric heads throughout southern Quebec. This study aims to use the wealth of available groundwater data available to better understand the resilience of groundwater resources to changes in meteorological and hydrological conditions. The study area is located between the St. Lawrence River and the Canada-USA border, and between the Quebec-Ontario border and Quebec City (36,000 km²). Available data consist of groundwater level time series from 81 observation wells (2000-2018; 43 in confined aquifers, 15 in semi-confined aquifers and 23 in unconfined aquifers), total flow rates from 179 hydrometric stations (1960-2017), and meteorological data from a spatially interpolated 10 km x 10 km grid (1960-2017). Statistical analyses (Mann Kendall and Sen’s slope) were used to understand if groundwater levels and flow rates are declining or rising, what is their short-, medium- and long-term memory and what are the geomorphological, land use, and climate controls of this reactivity. The results show that groundwater levels since 2007 exhibit statistically significant negative annual trends for most observation wells. Since 1960, river flow rates, total precipitation and air temperature all show significant increases. Trends calculated on five-year sliding windows confirm that groundwater levels and river flow rates are significantly correlated to the climate indices Southern Oscillation index (SOI), NINO-3 and Pacific Decadal Oscillation index (PDO). Autocorrelations of flow rates and groundwater level data indicate that rivers and aquifers have a short hydrological memory rarely extending beyond the hydrological year. Cross-correlations of flow rates and groundwater levels with temperature show high correlation coefficients with a lag of up to 60 days, indicating a season-long effect of temperature changes. As expected, cross-correlation analysis of the two data sets with precipitation shows smaller correlation coefficients and a shorter reaction time (10 days). Standard deviations of daily groundwater levels are significantly higher in shallower wells and in wells where groundwater levels are closer to the ground. This confirms the presence of highly dynamic shallow aquifers reacting rapidly to surface processes. Analyses are under way to test if spatially distributed parameters (e.g., geological setting, slope, land use) and well-related parameters (e.g.: depth, confined or unconfined) are explaining factors of trends and variations in groundwater levels and flow rates. One key observation from this study is that the RSESQ is highly valuable to understand groundwater dynamics and should be maintained on a long-term horizon. This detailed analysis has allowed to identify external influences (e.g., pumping) on some observation wells that do not reflect natural conditions and could be removed from the observation network. Recommendations also include the need for new observation wells in specific locations to improve the representativity of groundwater flow conditions in the study area.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".