An improved representation of ephemeral pool hydrology in a semi-distributed hydrologic model
Bibliographic record
Abstract
Ephemeral pools are seasonally flooded geographically isolated wetlands with distinct hydrology i.e., they are filled in winter and spring with inflow from snowmelt, and precipitation and dry out during summer. Ephemeral pools offer a variety of biodiversity benefits notably providing breeding habitat for several amphibian and invertebrate species. The quality of their ecosystem services is mainly controlled by their hydroperiod which is regulated by hydrology i.e., inflow /outflow of the pools. The classic water budget modeling approach with a simplified representation of the flow exchange between the pool and surface-subsurface zones may not adequately reveal their sensitivity to anthropogenic interventions and climatic changes. On the other hand, the generic volume-area-depth relationship of isolated wetlands in deterministic hydrologic models may not adequately reveal their dynamic water level fluctuations. The objective of this study, in the first place, is to improve the representation of ephemeral pools in the semi-distributed SWAT hydrological model, notably in the pothole module which is used for modeling isolated wetlands. The developed model will then be used to analyze the impact of land use and climate changes on dynamics of hydroperiods of ephemeral pools of the Saumon River watershed (68 km2) in the Canadian Shield of the Outaouais region (Quebec, Canada). A detailed bathymetry survey along with a long series (one to five years) of daily water level measurements available at ten pools allowed to replace the simplified linear volume-area relationship with the measured rating curve for the ephemeral pools in this region. The calibration process of the revised model is performed using the standard SWAT calibration code (SWAT-CUP) coupled to a Particle Swarm Optimization (PSO) algorithm adjusting evaporation and seepage coefficients of the revised module for all isolated wetlands of the region. This double calibration ensures representation of both the watershed hydrology (10 years of river flow rates) and the water level fluctuations in the pools. The simulation results show that the revised SWAT version can adequately reproduce the dynamic water level behavior of the monitored pools as well as streamflow discharges. The model is currently used with scenarios of human and climatic disturbances to understand their impact on the filling-drying cycle of ephemeral pools and on the integrated hydrologic system at the watershed scale.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".