Response of the water balance to climate change in the United States over the 20th and 21st centuries: Results from the VEMAP Phase 2 model intercomparisons
Bibliographic record
Abstract
Using the VEMAP Phase 2 data set, we tested the hypothesis that changes in climate would result in changes in the water balance as projected by four terrestrial ecosystem models: BIOME‐BGC, Century, LPJ, and MC1. We examined trends in runoff and actual evapotranspiration (AET), changes in runoff in relation to changes in precipitation, and differences in runoff ratios as produced by these models for 13 United States watersheds. Observed climate data were used as inputs for simulations covering 1895–1993. From 1994 to 2100, the Canadian Centre for Climate Modeling and Analysis (CGCM1) and the Hadley Centre for Climate Prediction and Research (HADCM2) general circulation models provided climate forcing. Runoff and AET trends were significantly positive in the majority of 13 watersheds examined. Percentage changes in runoff exceeded the underlying changes in precipitation and this amplification increased over time. Calculated runoff ratios showed model variability and differences based on the two GCM scenarios.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".