Assessing climate change impacts on water availability of snowmelt-dominated basins of the Upper Rio Grande basin
Bibliographic record
Abstract
Study region Upper Rio Grande, Colorado and New Mexico, USA. Study focus Climate change is predicted to further limit the water availability of the arid southwestern U.S. We use the snowmelt runoff model to evaluate impacts of climate change on snow covered area (SCA), streamflow timing and runoff volume. Simulations investigate four future conditions using models downscaled to existing climate stations. Twenty-four subbasins of the Upper Rio Grande containing appreciable snowmelt and a long-term gauging station are simulated. New hydrological insights for the region Future annual volume is 193–204 million m 3 more to 448–476 million m 3 less than the pre-climate change value of 2688 million m 3 . There is disparity between increased volume in wetter simulations (+7%) and decreased volume (−18%) in drier simulations. SCA on 1 April reduced by approximately 50% in all but the warmer/wetter climate. Peak flow is 14–24 days early in the future climates. Among the 24 subbasins there is considerable range in mean melt season SCA (−40% to −100%), total volume change (−30% to +57%) and runoff timing advancement indicating that climate change is best evaluated at the subbasin scale. Daily hydrographs show higher streamflow in March and April, but less from mid-May until the end of the water year. The large decrease in volume in May, June and July will compound water management challenges in the region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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 teacher head, 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".