Groundwater and surface water influences on streamflow in a mesoscale Precambrian Shield catchment
Bibliographic record
Abstract
Abstract Hydrologic research has increasingly recognized the importance of mesoscale studies to provide a fundamental understanding of how processes combine at scales relevant to water resource management. At the mesoscale, the influence of landscape heterogeneity including both natural and human‐altered conditions on streamflow generation is an open question, one to which analysis of stable water isotopes (SWI) is increasingly being applied. In this study, SWI surveys are used to better understand spatial and temporal patterns of source‐water contributions to streamflow in the Wistiwasing watershed (235 km 2 ) located near Callander Bay, Ontario, Canada, a Precambrian Shield headwater with mixed landuse (e.g. agriculture, forest). Biweekly surveys of surface water, groundwater and precipitation were conducted during May to September 2012, and samples were analysed for SWI (δ 18 O and δ 2 H) using a Picarro L2120‐ i . Maps of point‐scale surface water SWI were generated for each of the nine surveys, and an SWI isoscape, an interpolated contour map, was generated from groundwater observations. Based on a comparison of surface and groundwater SWI maps, regions of strong groundwater influence on streamflow were particularly identifiable during low‐flow, late‐summer conditions and corresponded with coarse‐textured glaciolacustrine deposits. Higher‐flow, early‐period conditions featured small SWI variation with values resembling long‐term groundwater recharge, a mix of snowmelt and spring/fall rains. Late‐period, low‐flow conditions indicated large spatial variability due to changing influences of groundwater and upstream surface water undergoing summertime evaporative enrichment of heavier isotopes. In this case study, SWI observations provide important insight into source‐water dynamics across a mesoscale watershed. Copyright © 2015 John Wiley & Sons, Ltd.
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 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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".