Assessment of a hydrologic model's reliability in simulating flow regime alterations in a changing climate
Bibliographic record
Abstract
Abstract It is a common practice to employ hydrologic models for assessing present and future states of watersheds and assess the degree of alterations for a range of hydrologic indicators. Previous studies indicate that the hydrologic model may not be able to replicate some of the indicators of interest, which raises questions on the reliability of model simulated changes. Hence, we initiated a study to evaluate the replicability of the streamflow changes by employing the widely used variable infiltration capacity hydrologic model for sub‐basins and mainstem of the Fraser River Basin, Canada. Given that the hydrologic regime of the region is known to be influenced by teleconnections to the Pacific Decadal Oscillation (PDO) and El Niño–Southern Oscillation (ENSO), we used hydrologic responses to the PDO and ENSO states as analogues for evaluating the model's ability to simulate climate‐induced changes. The results revealed that the qualitative patterns of response, such as lower flows for the warm PDO state compared to the cool state, and progressively higher flows for the warm, neutral and cool ENSO states, were generally well reproduced for most hydrologic indicators. Additionally, while the directions of change between the different PDO and ENSO states were mostly well replicated, the magnitude of change for some of the indicators showed considerable differences. Hence, replicability of both magnitude and direction of change need to be carefully examined before using the simulated indicators for assessing future hydrologic changes, and a reliable replication increases the confidence of projected changes. Copyright © 2016 Her Majesty the Queen in Right of Canada. Hydrological Processes. © 2016 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 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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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".