Stable isotope estimates of evaporation : inflow and water residence time for lakes across the United States as a tool for national lake water quality assessments
Bibliographic record
Abstract
We used water δ 2 H and δ 18 O from ca. 1000 lakes sampled in the 2007 U.S. Environmental Protection Agency's National Lakes Assessment (NLA) to assess two hydrological variables—evaporation as a percentage of inflow ( E : I ) and water residence time ( τ ) for summer 2007. Using a population survey design, sampled lakes were distributed across the conterminous U.S., and results were scaled to the inference population (∼50,000 U.S. lakes). These hydrologic variables were related to lake nutrients and biological condition to illustrate their usefulness in national water quality monitoring efforts. For 50% of lakes, evaporation was < 25% of inflow, with values ranging up to 113% during the 2007 summer. Residence time was < 0.52 yr for half of the lakes and < 1.12 yr for 75% of lakes. Categorizing lakes by flow regime, 66.1% of lakes were flow‐though lakes (60% or more of the water flows through the lake, E : I < 0.4), 33.6% were restricted‐basin lakes (40% or more of the lake inflow evaporates, 0.4 < E : I < 1), and < 0.3% were closed basin (all water entering the lake leaves through evaporation, E : I > 1). While climate patterns drove some of the spatial patterns of E : I and τ , variation in lake depth and watershed size (influencing precipitation volume) were also significant drivers. Lake hydrochemistry was strongly correlated to E : I and more weakly related to τ . Lakes in poor biological condition (based on a predictive model of planktonic taxa) were significantly more evaporated than lakes in good biological condition.
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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 | 0.001 | 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 | 0.000 |
| 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".