Storage dynamics simulations in prairie wetland hydrology models: evaluation and parameterization
Bibliographic record
Abstract
Abstract The contributing areas of streams in the Prairie regions of Canada and the northern U.S. are dominated by complexes of wetlands which store and release water. Prior research has suggested the existence of hysteresis between the total volume of water stored in prairie wetlands within a drainage basin and the basin's contributing area. To simulate the relationship between storage and contributing area in a way that accounts for hysteresis, two wetland hydrology models with vastly different levels of complexity were devised. The fully distributed Wetland Digital Elevation Model (DEM) Ponding Model (WDPM) applies simple fluxes of runoff and evaporation to a DEM of a prairie wetland complex. The parameterized Pothole Cascade Model (PCM) applies simulated fluxes of water to collections of conceptual models of wetlands and is less demanding in computations and data. Prior research showed that both models produced hysteretic relationships between water storage and contributing area, but the PCM produced smaller estimates of contributing area than did the WDPM, likely due to its spatial simplification. Using sequential remote sensing observations of wetland area after snowmelt, this study shows that the frequency distribution of the open water areas of prairie wetlands is similar to that produced by the WDPM when the wetlands are close to being completely filled. The remotely sensed observations show evidence of hysteresis in the open water area frequency distributions, as predicted by the fully distributed WDPM. To enable the parameterized PCM to produce the same type of hysteretic relationships as the WDPM, scaling relationships between the maximum area of a wetland and the area of upland draining into it were included. The parameterized PCM is suitable for application with prairie snow redistribution, snowmelt, infiltration, runoff and evapotranspiration routines as part of semi‐distributed hydrological modelling of prairie wetland basins such as that implemented in the Cold Regions Hydrological Model. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".