An integrated modelling framework of catchment‐scale ecohydrological processes: 1. Model description and tests over an energy‐limited watershed
Bibliographic record
Abstract
ABSTRACT The interactions between atmospheric, hydrological, and ecological processes at various spatial and temporal scales are not fully represented in most ecohydrological models. This first of a two‐part paper documents a fully integrated catchment‐scale ecohydrological model consisting of a three‐dimensional physically based hydrological model and a land surface model. This first part also presents a first application to test the model over an energy‐limited catchment (8.4 km2) of the Sleepers River watershed in Vermont. The physically based hydrological model (CATchment HYdrology, CATHY) describes three‐dimensional subsurface flow in variably saturated porous media and surface routing on hillslopes and in stream channels, whereas the land surface model (LSM), an augmented version of Noah LSM with multiple parameterization schemes (NoahMP), accounts for energy, water, and carbon flux exchanges between various land surface elements and the atmosphere. CATHY and NoahMP are coupled through exchanges of water fluxes and states. In the energy‐limited catchment of the Sleepers River watershed, where snowmelt runoff generation is the dominant hydrologic flux, the coupled CATHY/NoahMP model at both 90 and 30‐m surface grid resolutions, with minimal calibration, performs well in simulating the observed snow accumulation, and melt and subsequent snowmelt discharge. The Nash–Sutcliffe model efficiency of daily discharge is above 0.82 for both resolutions. The simulation at 90‐m resolution shows a marginal improvement over that at 30‐m resolution because of more elaborate calibration of model parameters. The coupled CATHY/NoahMP also shows a capability of simulating surface‐inundated area and distributed surface water height, although the accuracy of these simulations needs further evaluation. The CATHY/NoahMP model is thus also a potentially useful research tool for predicting flash flood and lake dynamics under climatic change. 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".