Assessment of climate change impacts at the catchment scale with a detailed hydrological model of surface‐subsurface interactions and comparison with a land surface model
Bibliographic record
Abstract
A process‐based model that incorporates hydrodynamic feedbacks between the land surface, soil, and groundwater zones is used to assess the sensitivity of the hydrological response (river discharge, aquifer recharge, and soil water storage) to future climate conditions. The analysis is based on the Intergovernmental Panel on Climate Change Special Report on Emissions Scenario A2 and the des Anglais catchment in southwestern Quebec (Canada). Application of the coupled hydrological model (CATHY) to the study basin revealed significant spatiotemporal variations in the river discharge response to climate change owing to a different partitioning between the overland runoff and base flow components of the hydrograph, with the latter alleviating the marked decrease in discharge during the summer period. A spatial analysis of recharge patterns shows that the greatest variations are expected to occur, throughout the year, in the southern portion of the catchment, where the elevations are highest. Compared to river discharge and aquifer recharge, the soil water storage volumes are less sensitive to climate changes. From a spatial analysis of soil moisture variations it was possible to observe organizational patterns that follow the topographic and pedologic characteristics of the catchment. In addition to these analyses, we also compare predictions obtained with the land surface scheme (CLASS) that is coupled to the regional climate model (CRCM) to those from the detailed catchment model for past and future climate change projections. An examination of the runoff revealed that CLASS produces higher estimates than CATHY of surface and subsurface runoff throughout the annual cycle for both past and future projections. For soil water storage, the two models are in general agreement in terms of the intra‐annual variability of moisture content at shallower soil layers, whereas a larger difference is found for the deepest layer, with CATHY predicting wetter soil conditions over the entire simulation period and moisture fluctuations of much smaller amplitude.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".