Modeling Streamflow Response to Persistent Drought in a Coastal Tropical Mountainous Watershed, Sierra Nevada De Santa Marta, Colombia
Bibliographic record
Abstract
Droughts constitute natural hazards that affect water supply for ecosystems and human livelihoods. In 2013–2016, the Caribbean experienced the worst drought since the 1950s, and climate projections for the southern Caribbean predict less rainfall by the end of the 21st century. We assessed streamflow response to drought for a watershed in the Colombian Caribbean by analyzing the effects of drought length and land cover on streamflow recovery. We generated a calibrated SWAT model and created annual and monthly drought scenarios from rainfall records. We used our model to predict water yield for selected land covers (wet forest, shade coffee, shrub, and dry forest) under drought conditions. Annual scenarios resulted in water yield reductions of ~15 mm month−1 (wet forest, coffee, and shrub) and 5 mm month−1 (dry forest) for the first month after a two-year drought. Maximum water yield reductions for monthly scenarios occurred after a 10-month drought and were ~100 mm month−1 (wet forest, coffee, and shrub) and 20 mm month−1 (dry forest). Streamflow recovered within nine months (annual scenarios), and two to eight months (monthly scenarios) after drought termination. Drought response seems to be conditioned by climatic factors (rainfall seasonality and spatial variability) and catchment properties.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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; both teacher heads agree on what is shown here.
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".